Relevant bibliographies by topics / Imagerie intelligente

Academic literature on the topic 'Imagerie intelligente'

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Published: 7 July 2024
Last updated: 7 July 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Imagerie intelligente":

1

Saigre-Tardif, Chloé, Rashid Faqiri, Hanting Zhao, Lianlin Li, and Philipp del Hougne. "Intelligent meta-imagers: From compressed to learned sensing." Applied Physics Reviews 9, no. 1 (March 2022): 011314. http://dx.doi.org/10.1063/5.0076022.

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Computational meta-imagers synergize metamaterial hardware with advanced signal processing approaches such as compressed sensing. Recent advances in artificial intelligence (AI) are gradually reshaping the landscape of meta-imaging. Most recent works use AI for data analysis, but some also use it to program the physical meta-hardware. The role of “intelligence” in the measurement process and its implications for critical metrics like latency are often not immediately clear. Here, we comprehensively review the evolution of computational meta-imaging from the earliest frequency-diverse compressive systems to modern programmable intelligent meta-imagers. We introduce a clear taxonomy in terms of the flow of task-relevant information that has direct links to information theory: compressive meta-imagers indiscriminately acquire all scene information in a task-agnostic measurement process that aims at a near-isometric embedding; intelligent meta-imagers highlight task-relevant information in a task-aware measurement process that is purposefully non-isometric. The measurement process of intelligent meta-imagers is, thus, simultaneously an analog wave processor that implements a first task-specific inference step “over-the-air.” We provide explicit design tutorials for the integration of programmable meta-atoms as trainable physical weights into an intelligent end-to-end sensing pipeline. This merging of the physical world of metamaterial engineering and the digital world of AI enables the remarkable latency gains of intelligent meta-imagers. We further outline emerging opportunities for cognitive meta-imagers with reverberation-enhanced resolution, and we point out how the meta-imaging community can reap recent advances in the vibrant field of metamaterial wave processors to reach the holy grail of low-energy ultra-fast all-analog intelligent meta-sensors.
2

Sun, Roger, Eric Deutsch, and Laure Fournier. "Intelligence artificielle et imagerie médicale." Bulletin du Cancer 109, no. 1 (January 2022): 83–88. http://dx.doi.org/10.1016/j.bulcan.2021.09.009.

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Caicedo Caicedo, Julio César, and José Nelson Pérez Castillo. "An intelligent web service for classifying digital imagery by using rough sets." Ingeniería e Investigación 30, no. 1 (January 1, 2010): 45–51. http://dx.doi.org/10.15446/ing.investig.v30n1.15206.

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Integrating recent developments in service-orientated computing, Web technologies and computational intelligence has facilitated the development of applications for solving complex problems in several fields of scientific and technological research. Rough sets theory provides a solid theoretical background within the computational intelligence (CI) field for the qualitative reasoning required for analysing datasets loaded with uncertainties due to the vagueness and lack of precision associated with them. This paper describes the development of an intelligent Web service to process digital imagery, demonstrating the benefits of rough sets theory in dealing with the flexible supervised classification of the pixels associated with them.
4

Kapilaratne, R. G. C. J., and S. Kakuta. "TOWARDS HIGH RESOLUTION FEATURE MAPPNG WITH SENTINEL-2 IMAGES." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023 (December 5, 2023): 137–44. http://dx.doi.org/10.5194/isprs-annals-x-1-w1-2023-137-2023.

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Abstract. High resolution feature mapping from medium resolution imageries gained special attention among remote sensing user community with the launch of Copernicus’ Sentinel-2 mission due to its capability to provide global coverage with relatively high revisit time at no cost. In this paper, we have examined and evaluated the potential of high resolution (2.5m) feature mapping from Sentinel-2 imageries with the aid of artificial intelligence. Generative adversarial network (GAN) is used as single image super resolution (SISR) technology in this study. And SPOT satellite imageries are used as corresponding high-resolution images. From qualitative and quantitative analysis of the experimental results found that spectral quality of the generated images is adequate for remote sensing applications. In conclusion, high resolution feature mapping from Sentinel-2 images found to be feasible to a greater extent for remote sensing applications.
5

Foucart, Jean-Michel, Augustin Chavanne, and Jérôme Bourriau. "Intelligence artificielle : le futur de l’Orthodontie ?" Revue d'Orthopédie Dento-Faciale 53, no. 3 (September 2019): 281–94. http://dx.doi.org/10.1051/odf/2019026.

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Nombreux sont les apports envisagés de l’Intelligence Artificielle (IA) en médecine. En orthodontie, plusieurs solutions automatisées sont disponibles depuis quelques années en imagerie par rayons X (analyse céphalométrique automatisée, analyse automatisée des voies aériennes) ou depuis quelques mois (analyse automatique des modèles numériques, set-up automatisé; CS Model +, Carestream Dental™). L’objectif de cette étude, en deux parties, est d’évaluer la fiabilité de l’analyse automatisée des modèles tant au niveau de leur numérisation que de leur segmentation. La comparaison des résultats d’analyse des modèles obtenus automatiquement et par l’intermédiaire de plusieurs orthodontistes démontre la fiabilité de l’analyse automatique; l’erreur de mesure oscillant, in fine, entre 0,08 et 1,04 mm, ce qui est non significatif et comparable avec les erreurs de mesures inter-observateurs rapportées dans la littérature. Ces résultats ouvrent ainsi de nouvelles perspectives quand à l’apport de l’IA en Orthodontie qui, basée sur le deep learning et le big data, devrait permettre, à moyen terme, d’évoluer vers une orthodontie plus préventive et plus prédictive.
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Makendran, C., M. Karthik, S. M. Jakir Hasan, M. Harivignesh, and G. Varun Raahul. "Designing an Intelligent Pavement Maintenance and Management System using Drone Imagery and Artificial Intelligence." MATEC Web of Conferences 393 (2024): 02005. http://dx.doi.org/10.1051/matecconf/202439302005.

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This paper presents the development of an innovative pavement maintenance and management system leveraging advanced drone imagery and Convolutional Neural Network (CNN) image classification. Our system is designed to perform 2D modelling of road surfaces using high-resolution images captured by drones. These images are then analysed by a CNN model specifically trained to detect and classify pavement damages in accordance with the IRC:82 'Code of Practice for Maintenance of Bituminous Surfaces of Highways'. The classification process identifies various types of road distresses such as cracks, potholes, and surface wear. Each identified distress is documented in a comprehensive report detailing the nature of the damage and recommending specific remedies as per IRC guidelines. Furthermore, the system categorizes the severity of the damages, facilitating the dispatch of these results to maintenance authorities for immediate action. This ensures that repair efforts are prioritized effectively, contributing to the maintenance of safer and higher quality roadways. By automating the detection and classification of road damages, this system not only accelerates the repair process but also plays a crucial role in reducing road accidents by maintaining better road conditions. This approach showcases the potential of integrating artificial intelligence and drone technology in the field of road maintenance, marking a significant step towards smarter and safer road infrastructure.
7

Wang, Hui, Hong Chang Ke, and Li Juan Zhang. "Calculus Method Research of Imagery Conceptual Network Based on Revision Calculus." Advanced Materials Research 317-319 (August 2011): 937–41. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.937.

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Through developing intelligent system of human-like thinking, national defense, economic, education, culture and so on will be impact. Constructing intelligence system of human-like intelligent mainly lies in how to effectively imitate the approach with which human use imagery to cognize. From psychological point of view, the process of cognitive is the transformation process of objects and attributes. Based on this thought, imagery of conceptual network is constructed based on imagery concept and attribute to store the overall planning information of imagery object conceptual. According to imagery conceptual network we build, calculus method imagery of conceptual network based on revision calculus is proposed to guide filling and revision of the nodes of imagery of conceptual network. According to the instance calculus given in the paper can be seen, the calculus method imagery conceptual network can fill and revise the nodes of imagery conceptual network, which can effectively imitate storing imagery and induction imagery of the human brain.
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Labazanova, Saida K., Timur G. Aygumov, and Marat Kh Mursaliev. "Issues with generative artificial intelligence tools." ITM Web of Conferences 59 (2024): 04007. http://dx.doi.org/10.1051/itmconf/20245904007.

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Technological progress thrives any industry with its correct implementation. Technological improvement further levels up implemented fields. Although, the results not always pleasing to the eye and pockets. The idea is that technology is and will have some issues, varying from mild to severe. In the era of refined technology, one shines out from the most, and it is artificial intelligence. Its capabilities are enormous and application thus vast. The innovation branched into the different tools, that it is hard for one to follow and use the new ones, that emerges almost daily. This article will be focusing on the generative tools that are capable of mimicking almost anything, starting from text and ending with long sequences of imageries. Above all on its issues. As an outcome of the last, the possible solutions will also be discussed.
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DAVIES, PHILIP H. J. "Imagery in the UK: Britain's troubled imagery intelligence architecture." Review of International Studies 35, no. 4 (October 2009): 957–69. http://dx.doi.org/10.1017/s0260210509990386.

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AbstractThis article examines the status, role and development of imagery intelligence in the UK government. It is argued that imagery intelligence occupies a subordinate and marginalised position compared to other forms of intelligence, chiefly from human sources and the interception of communications. The origins of that position are recounted, and the problems arising from internal struggles over control of imagery examined. It is concluded that the existing approach to imagery represents a serious problem and that a substantial restructuring and upgrading of imagery intelligence is essential if UK foreign policy decision-making is to be properly informed in the 21st Century.
10

Kunda, Maithilee. "AI, visual imagery, and a case study on the challenges posed by human intelligence tests." Proceedings of the National Academy of Sciences 117, no. 47 (November 23, 2020): 29390–97. http://dx.doi.org/10.1073/pnas.1912335117.

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Observations abound about the power of visual imagery in human intelligence, from how Nobel prize-winning physicists make their discoveries to how children understand bedtime stories. These observations raise an important question for cognitive science, which is, what are the computations taking place in someone’s mind when they use visual imagery? Answering this question is not easy and will require much continued research across the multiple disciplines of cognitive science. Here, we focus on a related and more circumscribed question from the perspective of artificial intelligence (AI): If you have an intelligent agent that uses visual imagery-based knowledge representations and reasoning operations, then what kinds of problem solving might be possible, and how would such problem solving work? We highlight recent progress in AI toward answering these questions in the domain of visuospatial reasoning, looking at a case study of how imagery-based artificial agents can solve visuospatial intelligence tests. In particular, we first examine several variations of imagery-based knowledge representations and problem-solving strategies that are sufficient for solving problems from the Raven’s Progressive Matrices intelligence test. We then look at how artificial agents, instead of being designed manually by AI researchers, might learn portions of their own knowledge and reasoning procedures from experience, including learning visuospatial domain knowledge, learning and generalizing problem-solving strategies, and learning the actual definition of the task in the first place.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Imagerie intelligente":

1

Pincet, Lancelot. "Dynamic excitation systems for quantitative and super-resolved fluorescence microscopy." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASP033.

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La microscopie de localisation de molécule unique (SMLM) est une technique optique super-résolue permettant d'observer des échantillons biologiques marqués par des fluorophores avec une résolution bien inférieure à la limite de diffraction. La qualité de cette imagerie dépend fortement de la capacité à observer les molécules de manière individuelle, ce qui nécessite un contrôle précis de la photophysique des fluorophores pour qu'ils émettent de manière décalée dans l'espace et le temps. Jusqu'à présent, les méthodes d'excitation dynamique visaient à produire une illumination uniforme sur des champs larges (200 um x 200 um). Cependant, ces types d'illumination rencontrent des difficultés pour imager les échantillons biologiques denses, comme les neurones, où la diversité de la densité de fluorophores entrave la génération d'un régime de molécule unique de qualité uniforme sur toute la zone observée. Pour résoudre ce problème, je propose une nouvelle approche qui ajuste dynamiquement l'illumination en fonction de la densité de l'échantillon. Cette méthode combine un nouveau système optique d'excitation tri-dynamique avec une boucle de rétroaction basée sur l'analyse de densité, bénéficiant d'une étude approfondie de la photophysique des fluorophores. Le système d'imagerie intelligent, où le motif d'excitation varie dans le temps, intègre un système de balayage 2D, un système de zoom variable et un laser. Ceci permet de générer une variété de cartes d'éclairement dynamiques pour s'adapter à l'échantillon observé et à la densité de localisations détectées localement. Cette nouvelle approche a été validée sur différents échantillons biologiques. De plus, le système d’excitation dynamique a également permis d’explorer des modalités d'imagerie d'échantillons vivants, telles que le MSIM ou le FRAP
Single Molecule Localization Microscopy (SMLM) is a super-resolution optical technique enabling the observation of biological samples labeled with fluorescent dyes at resolutions well below the diffraction limit. The quality of this imaging heavily relies on the ability to observe molecules individually, requiring precise control of fluorescent dye photophysics for them to emit with a high sparsity in both space and time. Until now, dynamic excitation methods aimed to produce uniform illumination over large fields (200 um x 200 um). However, these types of illumination encounter difficulties in imaging dense biological samples, such as neurons, where the diversity in dye density prevented the generation of a uniform single molecule regime across the entire observed area. To address this issue, I propose a new approach that dynamically adjusts illumination based on sample density. This method combines a novel tri-dynamic optical excitation system with a feedback loop based on density analysis, benefiting from an in-depth study of fluorescent dye photophysics. The intelligent imaging system, where the excitation pattern varies over time, integrates a 2D scanning system, a variable zoom system, and a laser. This allows for the generation of a variety of dynamically changing illumination patterns to adapt to the observed sample and the density of locally detected localizations. This new approach has been validated on various biological samples. Additionally, the dynamic excitation system has also been explored for live samples imaging techniques, such as MSIM or FRAP
2

Filali, Wassim. "Détection temps réel de postures humaines par fusion d'images 3D." Toulouse 3, 2014. http://thesesups.ups-tlse.fr/3088/.

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Cette thèse est centrée sur un projet de recherche en vision. Il s'agit d'un projet qui permet à des caméras intelligentes de comprendre dans quelle posture se trouve la personne filmée. Cela permet de savoir si la personne se porte bien ou si elle est dans une situation critique ou de danger. Les caméras ne doivent pas être connectées à un ordinateur, mais avoir toute l'intelligence embarquée dans la caméra même. Ce travail s'appuie sur des technologies récentes comme le capteur Kinect de la console de jeu. Ce type de capteur est un capteur de profondeur, c'est-à-dire que la caméra peut estimer la distance qui la sépare de chaque point de la scène. Notre contribution consiste à combiner plusieurs de ces caméras pour avoir une meilleure reconstruction de la posture de la personne. Nous avons créé une base de données d'images qui a permis d'apprendre au programme comment reconnaître les postures. Nous avons ajusté les bons paramètres à notre programme et on l'a comparé au programme du Kinect
This thesis is based on a computer vision research project. It is a project that allows smart cameras to understand the posture of a person. It allows to know if the person is alright or if it is in a critical situation or in danger. The cameras should not be connected to a computer but embed all the intelligence in the camera itself. This work is based on the recent technologies like the Kinect sensor of the game console. This sensor is a depth sensor, which means that the camera can estimate the distance to every point in the scene. Our contribution consists on combining multiple of these cameras to have a better posture reconstruction of the person. We have created a dataset of images to teach the program how to recognize postures. We have adjusted the right parameters and compared our program to the one of the Kinect
3

Burbano, Andres. "Système de caméras intelligentes pour l’étude en temps-réel de personnes en mouvement." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS139/document.

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Nous proposons un système dedétection et de suivi des personnes enmouvement dans des grands espaces. Notresolution repose sur un réseau de camérasintelligentes pour l'extraction desinformations spatio-temporelles despersonnes. Les caméras sont composées d'uncapteur 3D, d'un système embarqué et decommunication. Nous avons montrél'efficacité du placement des capteurs 3D enposition zénithale par rapport auxoccultations et variations d’échelle.Nous garantissons l'exécution des traitementsen temps-réel (~20 fps), permettantde détecter des déplacements rapides avecune précision jusqu’à 99 %, et capable d’unfiltrage paramétrique des cibles non désiréescomme les enfants ou les caddies.Nous avons réalisé une étude sur la viabilitétechnologique des résultats pour de grandsespaces, rendant la solution industrialisable
We propose a detection and trackingsystem of people moving in large spacessystem. Our solution is based on a network ofsmart cameras capable of retrievingspatiotemporal information from the observedpeople. These smart cameras are composed bya 3d sensor, an onboard system and acommunication and power supply system. Weexposed the efficacy of the overhead positionto decreasing the occlusion and the scale'svariation.Finally, we carried out a study on the use ofspace, and a global trajectories analysis ofrecovered information by our and otherssystems, able to track people in large andcomplex spaces
4

Panaïotis, Thelma. "Distribution du plancton à diverses échelles : apport de l'intelligence artificielle pour l'écologie planctonique." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS155.

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En tant que base des réseaux trophiques océaniques et élément clé de la pompe à carbone biologique, les organismes planctoniques jouent un rôle majeur dans les océans. Cependant, leur distribution à petite échelle, régie par les interactions biotiques entre organismes et les interactions avec les propriétés physico-chimiques des masses d'eau de leur environnement immédiat, est mal décrite in situ, en raison du manque d'outils d'observation adaptés. De nouveaux instruments d'imagerie in situ à haute résolution, combinés à des algorithmes d'apprentissage automatique pour traiter la grande quantité de données collectées, nous permettent aujourd'hui d'aborder ces échelles. La première partie de ce travail se concentre sur le développement méthodologique de deux pipelines automatisés basés sur l'intelligence artificielle. Ces pipelines ont permis de détecter efficacement les organismes planctoniques au sein des images brutes, et de les classer en catégories taxonomiques ou morphologiques. Dans une deuxième partie, des outils d'écologie numérique ont été appliqués pour étudier la distribution du plancton à différentes échelles, en utilisant trois jeux de données d'imagerie in situ. Tout d'abord, nous avons mis en évidence un lien entre les communautés planctoniques et les conditions environnementales à l'échelle globale. Ensuite, nous avons décrit la distribution du plancton et des particules à travers un front de méso-échelle, et mis en évidence des périodes contrastées pendant le bloom de printemps. Enfin, grâce aux données d'imagerie in situ à haute fréquence, nous avons étudié la distribution à fine échelle et la position préférentielle d’organismes appartement au groupe des Rhizaria, des protistes fragiles et peu étudiés, dont certains sont mixotrophes. Dans l’ensemble, ce travail démontre l'efficacité de l'imagerie in situ combinée à des approches d’intelligence artificielle pour comprendre les interactions biophysiques dans le plancton et les conséquences sur sa distribution à petite échelle
As the basis of oceanic food webs and a key component of the biological carbon pump, planktonic organisms play major roles in the oceans. However, their small-scale distribution − governed by biotic interactions between organisms and interactions with the physico-chemical properties of the water masses in their immediate environment − are poorly described in situ due to the lack of suitable observation tools. New instruments performing high resolution imaging in situ in combination with machine learning algorithms to process the large amount of collected data now allows us to address these scales. The first part of this work focuses on the methodological development of two automated pipelines based on artificial intelligence. These pipelines allowed to efficiently detect planktonic organisms within raw images, and classify them into taxonomical or morphological categories. Then, in a second part, numerical ecology tools have been applied to study plankton distribution at different scales, using three different in situ imaging datasets. First, we investigated the link between plankton community and environmental conditions at the global scale. Then, we resolved plankton and particle distribution across a mesoscale front, and highlighted contrasted periods during the spring bloom. Finally, leveraging high frequency in situ imaging data, we investigated the fine-scale distribution and preferential position of Rhizaria, a group of understudied, fragile protists, some of which are mixotrophic. Overall, these studies demonstrate the effectiveness of in situ imaging combined with artificial intelligence to understand biophysical interactions in plankton and distribution patterns at small-scale
5

Green, Steven Paul. "Intelligent Person Behaviour Analysis in Low Resolution Beach Video Imagery." Thesis, Griffith University, 2011. http://hdl.handle.net/10072/366650.

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Object detection in complex scenes plays an important role in many real world applications, such as scene analysis, security, traffic violation detection, and medical research. The Object Detection and Behaviour Classification (ODBC) system created from this PhD research, is ground-breaking and concentrates solely on the domain of people and behaviour detection in low resolution beach scene imagery. The video source for this research was obtained from Coastalwatch beach webcams, which are located throughout Australia. Current object detection systems, overall, utilise a similar methodology, following four main image processing procedures; 1) remove unwanted noise, 2) background extraction from an image scene, 3) segmentation of the objects from the scene, and 4) object classification into different class types. To my knowledge, there is no other past or current research studying behaviour detection in low resolution beach imagery, and therefore, my research leads the way in this domain. Information from beach imagery can provide important data for tourism promotions and beach safety. Analysis of people behaviour could assist in making decisions about promotions and beach amenities. Automated beach systems may provide constant monitoring of a beach, by detecting people entering the ocean in a flagged or non-flagged area of a beach. This may also provide an early warning system to assist lifeguards in protecting swimmers in a beach area.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information and Communication Technology
Science, Environment, Engineering and Technology
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Vétil, Rebeca. "Artificial Intelligence Methods to Assist the Diagnosis of Pancreatic Diseases in Radiology." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT014.

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Avec l’augmentation de son incidence et son taux de survie à cinq ans (9%), le cancer du pancréas pourrait devenir la troisième cause de décès par cancer d’ici 2025.Ces chiffres sont notamment dus aux diagnostics tardifs, limitant les options thérapeutiques. Cette thèse vise à assister les radiologues dans le diagnostic du cancer du pancréas sur des images scanner grâce à des outils d’intelligence artificielle (IA) qui faciliteraient un diagnostic précoce. Pour atteindre ces objectifs, trois pistes de recherche ont été explorées. Premièrement, une méthode de segmentation automatique du pancréas a été développée. Le pancréas présentant une forme allongée et des extrémités subtiles, la méthode proposée utilise des informations géométriques pour ajuster localement la sensibilité de la segmentation. Deuxièmement, une méthode réalise la détection des lésions et de la dilatation du canal pancréatique principal (CPP), deux signes cruciaux du cancer du pancréas. La méthode proposée commence par segmenter le pancréas, les lésions et le CPP. Ensuite, des caractéristiques quantitatives sont extraites des segmentations prédites puis utilisées pour prédire la présence d’une lésion et la dilatation du CPP. La robustesse de la méthode est de montrer sur une base externe de 756 patients. Dernièrement, afin de permettre un diagnostic précoce, deux approches sont proposées pour détecter des signes secondaires. La première utilise un grand nombre de masques de segmentation de pancréas sains pour apprendre un modèle normatif des formes du pancréas. Ce modèle est ensuite exploité pour détecter des formes anormales, en utilisant des méthodes de détection d’anomalies avec peu ou pas d’exemples d’entraînement. La seconde approche s’appuie sur deux types de radiomiques : les radiomiques profonds (RP), extraits par des réseaux de neurones profonds, et les radiomiques manuels (RM), calculés à partir de formules prédéfinies. La méthode extrait des RP non redondants par rapport à un ensemble prédéterminé de RM afin de compléter l’information déjà contenue. Les résultats montrent que cette méthode détecte Efficacement quatre signes secondaires : la forme anormale, l’atrophie, l’infiltration de graisse et la sénilité. Pour élaborer ces méthodes, une base de données de 2800 examens a été constituée, ce qui en fait l’une des plus importantes pour la recherche en IA sur le cancer du pancréas
With its increasing incidence and its five- year survival rate (9%), pancreatic cancer could be- come the third leading cause of cancer-related deaths by 2025. These figures are primarily attributed to late diagnoses, which limit therapeutic options. This the- sis aims to assist radiologists in diagnosing pancrea- tic cancer through artificial intelligence (AI) tools that would facilitate early diagnosis. Several methods have been developed. First, a method for the automatic segmentation of the pancreas on portal CT scans was developed. To deal with the specific anatomy of the pancreas, which is characterized by an elonga- ted shape and subtle extremities easily missed, the proposed method relied on local sensitivity adjust- ments using geometrical priors. Then, the thesis tack- led the detection of pancreatic lesions and main pan- creatic duct (MPD) dilatation, both crucial indicators of pancreatic cancer. The proposed method started with the segmentation of the pancreas, the lesion and the MPD. Then, quantitative features were extracted from the segmentations and leveraged to predict the presence of a lesion and the dilatation of the MPD. The method was evaluated on an external test cohort comprising hundreds of patients. Continuing towards early diagnosis, two strategies were explored to de- tect secondary signs of pancreatic cancer. The first approach leveraged large databases of healthy pan- creases to learn a normative model of healthy pan- creatic shapes, facilitating the identification of anoma- lies. To this end, volumetric segmentation masks were embedded into a common probabilistic shape space, enabling zero-shot and few-shot abnormal shape de- tection. The second approach leveraged two types of radiomics: deep learning radiomics (DLR), extracted by deep neural networks, and hand-crafted radiomics (HCR), derived from predefined formulas. The propo- sed method sought to extract non-redundant DLR that would complement the information contained in the HCR. Results showed that this method effectively de- tected four secondary signs of pancreatic cancer: ab- normal shape, atrophy, senility, and fat replacement. To develop these methods, a database of 2800 exa- minations has been created, making it one of the lar- gest for AI research on pancreatic cancer
7

Aberni, Yassir. "Algorithmes de reconnaissance biométrique multispectrale par l’empreinte et les veines palmaires." Electronic Thesis or Diss., Paris 8, 2021. http://www.theses.fr/2021PA080083.

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La biométrie devient de plus en plus une technologie importante pour améliorer la sécurité et apporter des solutions aux services nécessitant une authentification et/ou une protection des données. De nombreux traits biométriques ont été étudiés et utilisés pour la reconnaissance biométrique et l’empreinte palmaire en est un exemple. Bien que de nombreuses méthodes de reconnaissance par l’empreinte palmaire aient été proposées et appliquées avec succès, la plupart n’utilise généralement que les images prises à la lumière naturelle. Il est difficile d’améliorer encore la précision de la reconnaissance sur la base de ces images palmaires en raison des limitations liées à la lumière naturelle, parmi ces limitations on peut citer la capacité des attaques par usurpation d’identité, la dégradation des empreintes palmaires avec le temps en raison de plusieurs facteurs tels que l’environnement, l’origine ethnique ou l’âge. L’imagerie multi-spectrale a donc été utilisée pour surmonter ces limitations. Dans cette thèse, nous proposons de nouveaux algorithmes de reconnaissance biométrique à base de modalités physiologiques non visibles à l’œil nu, appelées cachées, issues de l’imagerie multi-spectrale, en particulier les veines palmaires. À cet effet, nous avons élaboré de nouvelles méthodes de reconnaissance biométrique par l’empreinte et les veines palmaires basées sur le codage compétitif utilisant un modèle binaire local multi-échelles appliqué à des images extraites avec une technique d’optimisation par colonies de fourmis. De nouvelles approches d’appariement pour la décision à base des métriques de divergence et de distance, ont été proposées pour quantifier la similitude entre les images de caractéristiques. Nous avons aussi proposé une autre nouvelle méthode basée sur un réseau neuronal convolutif en adaptant l’architecture ZFNet. Les expérimentations réalisées et l’étude comparative avec l’état de l’art, montrent l’efficacité de nos différentes méthodes pour les modes identification et vérification
Biometrics is increasingly becoming an important technology to improve security and bring solutions to services requiring authentication and/or data protection. Several biometric traits have been studied and used for biometric recognition, such as palm prints. Although many recognition methods based on the palm print have been proposed and successfully applied; where most of them generally uses only the images acquired in natural light. It is difficult to further improve the accuracy of recognition based on these palm print images due to limitations related to natural light, including the ability of identity theft attacks, degradation of palm prints over time due to several factors such as environment, ethnicity or age. Multi-spectral imaging has therefore been used to overcome these limitations. In this thesis, we propose novel biometric recognition algorithms based on physiological modalities not visible to the naked eye, called hidden, from multi-spectral imaging such as palm veins. To this end, we have developed novel biometric recognition methods using palm print and palm veins based on competitive coding using a local multiscale binary model applied on images extracted with an an ant colony optimization technique. Novel matching approaches for decision based on divergence and distance metrics have been proposed to quantify the similarity between feature images. We also proposed another novel method based on a convolutional neural network by adapting the ZFNet architecture. The experiments carried out and the comparative study with the state-of-the art, show the effectiveness of our different proposed methods for the identification and verification modes
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Alves, de Lima Danilo. "Sensor-based navigation applied to intelligent electric vehicles." Thesis, Compiègne, 2015. http://www.theses.fr/2015COMP2191/document.

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La navigation autonome des voitures robotisées est un domaine largement étudié avec plusieurs techniques et applications dans une démarche coopérative. Elle intègre du contrôle de bas niveau jusqu’à la navigation globale, en passant par la perception de l’environnement, localisation du robot, et autres aspects dans une approche référencée capteurs. Bien qu’il existe des travaux très avancés, ils présentent encore des problèmes et limitations liés aux capteurs utilisés et à l’environnement où la voiture est insérée.Ce travail aborde le problème de navigation des voitures robotisées en utilisant des capteurs à faible coût dans des milieux urbains. Dans cette thèse, nous avons traité le problème concernant le développement d’un système global de navigation autonome référencée capteur appliqué à un véhicule électrique intelligent, équipé avec des caméras et d’autres capteurs. La problématique traitée se décline en trois grands domaines de la navigation robotique : la perception de l’environnement, le contrôle de la navigation locale et la gestion de la navigation globale. Dans la perception de l’environnement, une approche de traitement d’image 2D et 3D a été proposé pour la segmentation de la route et des obstacles. Cette méthode est appliquée pour extraire aussi des caractéristiques visuelles, associées au milieu de la route, pour le contrôle de la navigation locale du véhicule. Avec les données perçues, une nouvelle méthode hybride de navigation référencée capteur et d’évitement d’obstacle a été appliquée pour le suivi de la route. Cette méthode est caractérisée par la validation d’une stratégie d’asservissement visuel (contrôleur délibératif) dans une nouvelle formulation de la méthode “fenêtre dynamique référencée image" (Dynamic Window Approach - DWA, en anglais) (contrôleur réactif). Pour assurer la navigation globale de la voiture, nous proposons l’association des données de cartes numériques afin de gérer la navigation locale dans les points critiques du chemin, comme les intersections de routes. Des essais dans les scénarios difficiles, avec une voiture expérimentale, et aussi en environnement simulé, montrent la viabilité de la méthode proposée
Autonomous navigation of car-like robots is a large domain with several techniques and applications working in cooperation. It ranges from low-level control to global navigation, passing by environment perception, robot localization, and many others in asensor-based approach. Although there are very advanced works, they still presenting problems and limitations related to the environment where the car is inserted and the sensors used. This work addresses the navigation problem of car-like robots based on low cost sensors in urban environments. For this purpose, an intelligent electric vehicle was equipped with vision cameras and other sensors to be applied in three big areas of robot navigation : the Environment Perception, Local Navigation Control, and Global Navigation Management. In the environment perception, a 2D and 3D image processing approach was proposed to segment the road area and detect the obstacles. This segmentation approach also provides some image features to local navigation control.Based on the previous detected information, a hybrid control approach for vision based navigation with obstacle avoidance was applied to road lane following. It is composed by the validation of a Visual Servoing methodology (deliberative controller) in a new Image-based Dynamic Window Approach (reactive controller). To assure the car’s global navigation, we proposed the association of the data from digital maps in order tomanage the local navigation at critical points, like road intersections. Experiments in a challenging scenario with both simulated and real experimental car show the viabilityof the proposed methodology
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Rebaud, Louis. "Whole-body / total-body biomarkers in PET imaging." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST047.

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Cette thèse, réalisée en partenariat avec l'Institut Curie et Siemens Healthineers, explore l'utilisation de l'imagerie par tomographie par émission de positrons (TEP) pour le pronostic du cancer, en se concentrant sur les lymphomes non hodgkiniens, en particulier le lymphome folliculaire (FL) et le lymphome diffus à grandes cellules B (DLBCL). Partant de l'hypothèse que les biomarqueurs actuels calculés dans les images TEP sous-utilisent leur richesse en informations, ce travail se concentre sur la recherche de nouveaux biomarqueurs en imagerie TEP corps entier. Une première approche manuelle a permis de valider une caractéristique précédemment identifiée (fragmentation de la tumeur) et d'explorer l'importance pronostique de l'atteinte splénique dans les DLBCL, en constatant que le volume de l'atteinte splénique ne permet pas de stratifier davantage les patients présentant une telle atteinte. Pour dépasser les limites empiriques de la recherche manuelle, une méthode d'identification semi-automatique des caractéristiques a été mise au point. Elle consiste à extraire automatiquement des milliers de biomarqueurs candidats et à les tester à l'aide d'un pipeline de sélection conçu pour trouver des caractéristiques quantifiant de nouvelles informations pronostiques. Les biomarqueurs sélectionnés ont ensuite été analysés et recodés de manière plus simple et plus intuitive. Cette approche a permis d'identifier 22 nouveaux biomarqueurs basés sur l'image, qui reflètent des informations biologiques sur les tumeurs, mais aussi l'état de santé général du patient. Parmi eux, 10 caractéristiques se sont avérées pronostiques à la fois pour les patients atteints de FL que pour ceux souffrant de DLBCL. La thèse aborde également le défi que représente l'utilisation de ces caractéristiques dans la pratique clinique, en proposant le modèle ICARE (Individual Coefficient Approximation for Risk Estimation). Ce modèle d'apprentissage automatique, conçu pour réduire le surapprentissage et améliorer la généralisation, a démontré son efficacité dans le cadre du challenge HECKTOR 2022 visant à prédire le risque de rechute de patients atteints de cancer des voies aérodigestives supérieures à partir de leurs images TEP. Ce modèle s'est également avéré plus résistant au surapprentissage que d'autres méthodes d'apprentissage automatique lors d'une comparaison exhaustive sur un benchmark de 71 jeux de données médicales. Ces développements ont été implémentés dans une extension logicielle d'un prototype développé par Siemens Healthineers
This thesis in partnership with Institut Curie and Siemens Healthineers explores the use of Positron Emission Tomography (PET) for cancer prognosis, focusing on non-Hodgkin lymphomas, especially follicular lymphoma (FL) and diffuse large B cell lymphoma (DLBCL). Assuming that current biomarkers computed in PET images overlook significant information, this work focuses on the search for new biomarkers in whole-body PET imaging. An initial manual approach validated a previously identified feature (tumor fragmentation) and explored the prognostic significance of splenic involvement in DLBCL, finding that the volume of splenic involvement does not further stratify patients with such an involvement. To overcome the empirical limitations of the manual search, a semi-automatic feature identification method was developed. It consisted in the automatic extraction of thousands of candidate biomarkers and there subsequent testing by a selection pipeline design to identify features quantifying new prognostic information. The selected biomarkers were then analysed and re-encoded in simpler and more intuitive ways. Using this approach, 22 new image-based biomarkers were identified, reflecting biological information about the tumours, but also the overall health status of the patient. Among them, 10 features were found prognostic of both FL and DLBCL patient outcome. The thesis also addresses the challenge of using these features in clinical practice, proposing the Individual Coefficient Approximation for Risk Estimation (ICARE) model. This machine learning model, designed to reduce overfitting and improve generalizability, demonstrated effectiveness in the HECKTOR 2022 challenge for predicting outcomes from head and neck cancer patients [18F]-PET/CT scans. This model was also found to overfit less than other machine learning methods on an exhaustive comparison using a benchmark of 71 medical datasets. All these developments were implemented in a software extension of a prototype developed by Siemens Healthineers
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Christie, Marc. "Spécification de trajectoires de caméra sous contraintes." Nantes, 2003. http://www.theses.fr/2003NANT2116.

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Books on the topic "Imagerie intelligente":

1

United States. Defense Intelligence Agency, ed. Imagery analysts: Directorate for Imagery Exploitation, Directorate for Foreign Intelligence. [Washington, D.C.]: Defense Intelligence Agency, 1987.

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Beaulieu, Danie. Techniques d'Impact pour grandir: Illustrations pour développer l'intelligence émotionnelle chez les adultes. 3rd ed. Le Gardeur, Québec: Impact!, 2006.

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Beaulieu, Danie. Techniques d'Impact pour grandir: Illustrations pour développer l'intelligence émotionnelle chez les enfants. 4th ed. Le Gardeur, Québec: Impact!, 2006.

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Beaulieu, Danie. Techniques d'Impact pour grandir: Illustrations pour développer l'intelligence émotionnelle chez les enfants. Lac Beauport, Québec: Éditions Académie impact, 2000.

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Beaulieu, Danie. Techniques d'impact pour grandir: Des illustrations pour développer l'intelligence émotionnelle chez les enfants. Montréal: Éditions Québecor, 2010.

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Lefébure, Francis. Phosphenism: The art of visualisation developing memory and intelligence. Church Crookham, U.K: Psychotechnic Publications, 1990.

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Wendy, Seider, and Goddard Space Flight Center, eds. Declassified Intelligence Satellite Photography (DISP) coverage of Antarctica. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1998.

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Great Britain. Parliament. House of Commons. Defence Committee. Fifth Report [session 1999-2000]: The Defence Geographic and Intelligence Agency : report and proceedings of the Committee with minutes of evidence and appendices. London: The Stationery Office, 2000.

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Great Britain. Parliament. House of Commons. Defence Committee. Fifth report: Procurement of major defence equipment : report and appendices, together with the proceedings of the Committee, minutes of evidence and appendices. London: H.M.S O., 1988.

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Wenger, Win. The Einstein factor: A proven new method for increasing your intelligence. Rocklin, CA: Prima Pub., 1996.

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Book chapters on the topic "Imagerie intelligente":

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Kok, Vernon, Nontokozo Mpofu, and Micheal Olusanya. "Severity Estimation of Potholes in Imagery Using Convolutional Neural Networks." In Artificial Intelligence in Intelligent Systems, 658–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77445-5_60.

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Rosenbloom, Paul S. "Extending Mental Imagery in Sigma." In Artificial General Intelligence, 272–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35506-6_28.

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Chouhan, Avinash, Dibyajyoti Chutia, and P. L. N. Raju. "Deep Learning Applications on Very High-Resolution Aerial Imagery." In Artificial Intelligence, 61–80. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003140351-8.

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Chouhan, Avinash, Dibyajyoti Chutia, and P. L. N. Raju. "Deep Learning Applications on Very High-Resolution Aerial Imagery." In Artificial Intelligence, 61–80. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003140351-8.

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Kaur, Satwinder, Bhawna Goyal, and Ayush Dogra. "Denoising Hyperspectral Imageries with Split-Bregman Iteration Scheme." In Intelligent Systems Design and Applications, 986–1001. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96308-8_92.

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Nguyen, Phuoc, Dat Tran, Xu Huang, and Wanli Ma. "Motor Imagery EEG-Based Person Verification." In Advances in Computational Intelligence, 430–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38682-4_46.

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Walker, James R. "The Rise of GEOINT: Technology, Intelligence and Human Rights." In Visual Imagery and Human Rights Practice, 67–88. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75987-6_5.

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Zhang, Yan, and Yanwei Ju. "Spatially Variant Mixtures of Multiscale ARMA Model for SAR Imagery Segmentation." In Artificial Intelligence and Computational Intelligence, 398–404. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23887-1_50.

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Zhao, Liaoying, Yinhe Shen, and Xiaorun Li. "Kernel Oblique Subspace Projection Approach for Target Detection in Hyperspectral Imagery." In Artificial Intelligence and Computational Intelligence, 422–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16530-6_50.

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Kim, Shin Hyoung, Jong Whan Jang, Seung Phil Lee, and Jae Ho Choi. "Accurate Contouring Technique for Object Boundary Extraction in Stereoscopic Imageries." In Computational Intelligence and Security, 869–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596981_127.

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Conference papers on the topic "Imagerie intelligente":

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Plebe, Alice, Riccardo Donà, Gastone Pietro Papini Rosati, and Mauro Da Lio. "Mental Imagery for Intelligent Vehicles." In 5th International Conference on Vehicle Technology and Intelligent Transport Systems. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007657500002179.

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Plebe, Alice, Riccardo Donà, Gastone Pietro Papini Rosati, and Mauro Da Lio. "Mental Imagery for Intelligent Vehicles." In 5th International Conference on Vehicle Technology and Intelligent Transport Systems. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007657500430051.

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Bindela, H. V. R., K. C. Yedubati, R. R. Gosula, E. Snir, and B. Rahmani. "Heart Failure Prediction Using Artificial Intelligence Methods." In 2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE, 2023. http://dx.doi.org/10.1109/aipr60534.2023.10440664.

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Noboa, Nicholas S., John W. Von Holle, Paul A. Brown, and John M. Irvine. "Utilization of Artificial Intelligence in Automated Image Analysis." In 2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE, 2022. http://dx.doi.org/10.1109/aipr57179.2022.10092210.

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Esposito, Marco, and Alessandro Zuccaro Marchi. "HyperCube the intelligent hyperspectral imager." In 2015 IEEE Metrology for Aerospace (MetroAeroSpace). IEEE, 2015. http://dx.doi.org/10.1109/metroaerospace.2015.7180716.

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Madison, Richard, and Yuetian Xu. "Tactical geospatial intelligence from full motion video." In 2010 IEEE Applied Imagery Pattern Recognition Workshop (AIPR 2010). IEEE, 2010. http://dx.doi.org/10.1109/aipr.2010.5759699.

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Endsley, William R. "General Imagery Intelligence Training System (GIITS)." In 29th Annual Technical Symposium, edited by Paul A. Henkel and Francis R. LaGesse. SPIE, 1985. http://dx.doi.org/10.1117/12.949637.

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Specht, David, Charles Johnson, Nidhal Bouaynaya, and Ghulam Rasool. "Intelligent Helipad Detection from Satellite Imagery." In Vertical Flight Society 77th Annual Forum & Technology Display. The Vertical Flight Society, 2021. http://dx.doi.org/10.4050/f-0077-2021-16856.

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Location data about U.S. heliports is often inaccurate or nonexistent in the FAA's databases, which leaves pilots and air ambulance operators with inaccurate information about where to find safe landing zones. In the 2018 FAA Reauthorization Act, Congress required the FAA to collect better information from the helicopter industry under part 157, which covers the construction, alteration, activation and deactivation of airports and heliports. At the same time, there is no requirement to report private helipads to the FAA when constructed or removed, and some public heliports do not have up to date records. This paper proposes an autonomous system that can authenticate the coordinates in the FAA master database, as well as search for helipads in a designated large area. The proposed system is based on a convolutional neural network model that learns optimal helipad features from the data. We used the FAA's 5010 database and others to construct a benchmark database of rotocraft landing sites. The database consists of 9,324 aerial images, containing helipads, helistops, helidecks, and helicopter runways in rural and urban areas, as well as negative examples, such as rooftop buildings and fields. The dataset was then used to train various state-of-the-art convolutional neural network models. The outperforming model, EfficientNet-bθ, achieved nearly 95% accuracy on the validation set.
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Huguenin, Robert L., Michael S. Bouchard, Mo-Hwa Wang, and Mark A. Karaska. "Automated intelligent distillation of hyperspectral imagery." In SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, edited by Michael R. Descour and Sylvia S. Shen. SPIE, 1999. http://dx.doi.org/10.1117/12.366269.

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Wildenstein, Diego, and Alan D. George. "Towards Intelligent Compression of Hyperspectral Imagery." In 2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2021. http://dx.doi.org/10.1109/conecct52877.2021.9622585.

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Reports on the topic "Imagerie intelligente":

1

McAuley, Cheryl D. STRATEGIC IMPLICATIONS OF IMAGERY INTELLIGENCE. Fort Belvoir, VA: Defense Technical Information Center, March 2005. http://dx.doi.org/10.21236/ada432777.

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Stafford, Ann E. Reserve Component Contribution to Imagery Intelligence. Fort Belvoir, VA: Defense Technical Information Center, May 2003. http://dx.doi.org/10.21236/ada416241.

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Hofer, Martin, Tomas Sako, Arturo Martinez Jr., Mildred Addawe, Joseph Bulan, Ron Lester Durante, and Marymell Martillan. Applying Artificial Intelligence on Satellite Imagery to Compile Granular Poverty Statistics. Asian Development Bank, December 2020. http://dx.doi.org/10.22617/wps200432-2.

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This study outlines a computational framework to enhance the spatial granularity of government-published poverty estimates, citing data from the Philippines and Thailand. Computer vision techniques were applied on publicly available medium resolution satellite imagery, household surveys, and census data from the two countries. The results suggest that even using publicly accessible satellite imagery, predictions generally aligned with the distributional structure of government-published poverty estimates after calibration. The study further examines the robustness of the resulting estimates to user-specified algorithmic parameters and model specifications.
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Cook, Paul J. Imagery and Measurement and Signatures Intelligence Support to Military Operations on Urbanized Terrain. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada419915.

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Eyes, Douglas J. The National Imagery and Mapping Agency: Harnessing Geographic and Imagery Intelligence in Support of the 21st Century Joint Force Commander. Fort Belvoir, VA: Defense Technical Information Center, February 1997. http://dx.doi.org/10.21236/ada324984.

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SAINI, RAVINDER, AbdulKhaliq Alshadid, and Lujain Aldosari. Investigation on the application of artificial intelligence in prosthodontics. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2022. http://dx.doi.org/10.37766/inplasy2022.12.0096.

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Review question / Objective: 1. Which artificial intelligence techniques are practiced in dentistry? 2. How AI is improving the diagnosis, clinical decision making, and outcome of dental treatment? 3. What are the current clinical applications and diagnostic performance of AI in the field of prosthodontics? Condition being studied: Procedures for desktop designing and fabrication Computer-aided design (CAD/CAM) in particular have made their way into routine healthcare and laboratory practice.Based on flat imagery, artificial intelligence may also be utilized to forecast the debonding of dental repairs. Dental arches in detachable prosthodontics may be categorized using Convolutional neural networks (CNN). By properly positioning the teeth, machine learning in CAD/CAM software can reestablish healthy inter-maxillary connections. AI may assist with accurate color matching in challenging cosmetic scenarios that include a single central incisor or many front teeth. Intraoral detectors can identify implant placements in implant prosthodontics and instantly input them into CAD software. The design and execution of dental implants could potentially be improved by utilizing AI.
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Thegeya, Aaron, Thomas Mitterling, Arturo Martinez Jr, Joseph Albert Niño Bulan, Ron Lester Durante, and Jayzon Mag-atas. Application of Machine Learning Algorithms on Satellite Imagery for Road Quality Monitoring: An Alternative Approach to Road Quality Surveys. Asian Development Bank, December 2022. http://dx.doi.org/10.22617/wps220587-2.

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This paper examines the feasibility of using satellite imagery and artificial intelligence to develop an efficient and cost-effective way to determine and predict the condition of roads in the Asia and Pacific region. The paper notes that collecting information on road quality is difficult, particularly in harder to reach middle- and low-income areas, and explains why this method offers an alternative. It shows how the study’s preliminary algorithm was created using satellite imagery and existing road roughness data from the Philippines. It assesses the accuracy rate and finds it sufficient for the preliminary identification of poor to bad roads. It notes that additional enhancements are needed to increase its prediction accuracy and make it more robust.
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Courtney, Peter. The Use of National Imagery Intelligence Assets to Obtain Battle Damage Assessment of Tactical Battlefield Targets. Fort Belvoir, VA: Defense Technical Information Center, February 2001. http://dx.doi.org/10.21236/ada389904.

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Murray, Chris, Keith Williams, Norrie Millar, Monty Nero, Amy O'Brien, and Damon Herd. A New Palingenesis. University of Dundee, November 2022. http://dx.doi.org/10.20933/100001273.

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Robert Duncan Milne (1844-99), from Cupar, Fife, was a pioneering author of science fiction stories, most of which appeared in San Francisco’s Argonaut magazine in the 1880s and ’90s. SF historian Sam Moskowitz credits Milne with being the first full-time SF writer, and his contribution to the genre is arguably greater than anyone else including Stevenson and Conan Doyle, yet it has all but disappeared into oblivion. Milne was fascinated by science. He drew on the work of Scottish physicists and inventors such as James Clark Maxwell and Alexander Graham Bell into the possibilities of electromagnetic forces and new communications media to overcome distances in space and time. Milne wrote about visual time-travelling long before H.G. Wells. He foresaw virtual ‘tele-presencing’, remote surveillance, mobile phones and worldwide satellite communications – not to mention climate change, scientific terrorism and drone warfare, cryogenics and molecular reengineering. Milne also wrote on alien life forms, artificial immortality, identity theft and personality exchange, lost worlds and the rediscovery of extinct species. ‘A New Palingenesis’, originally published in The Argonaut on July 7th 1883, and adapted in this comic, is a secular version of the resurrection myth. Mary Shelley was the first scientiser of the occult to rework the supernatural idea of reanimating the dead through the mysterious powers of electricity in Frankenstein (1818). In Milne’s story, in which Doctor S- dissolves his terminally ill wife’s body in order to bring her back to life in restored health, is a striking, further modernisation of Frankenstein, to reflect late-nineteenth century interest in electromagnetic science and spiritualism. In particular, it is a retelling of Shelley’s narrative strand about Frankenstein’s aborted attempt to shape a female mate for his creature, but also his misogynistic ambition to bypass the sexual principle in reproducing life altogether. By doing so, Milne interfused Shelley’s updating of the Promethean myth with others. ‘A New Palingenesis’ is also a version of Pygmalion and his male-ordered, wish-fulfilling desire to animate his idealised female sculpture, Galatea from Ovid’s Metamorphoses, perhaps giving a positive twist to Orpheus’s attempt to bring his corpse-bride Eurydice back from the underworld as well? With its basis in spiritualist ideas about the soul as a kind of electrical intelligence, detachable from the body but a material entity nonetheless, Doctor S- treats his wife as an ‘intelligent battery’. He is thus able to preserve her personality after death and renew her body simultaneously because that captured electrical intelligence also carries a DNA-like code for rebuilding the individual organism itself from its chemical constituents. The descriptions of the experiment and the body’s gradual re-materialisation are among Milne’s most visually impressive, anticipating the X-raylike anatomisation and reversal of Griffin’s disappearance process in Wells’s The Invisible Man (1897). In the context of the 1880s, it must have been a compelling scientisation of the paranormal, combining highly technical descriptions of the Doctor’s system of electrically linked glass coffins with ghostly imagery. It is both dramatic and highly visual, even cinematic in its descriptions, and is here brought to life in the form of a comic.
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Ruby, Jeffrey, Richard Massaro, John Anderson, and Robert Fischer. Three-dimensional geospatial product generation from tactical sources, co-registration assessment, and considerations. Engineer Research and Development Center (U.S.), February 2023. http://dx.doi.org/10.21079/11681/46442.

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Abstract:
According to Army Multi-Domain Operations (MDO) doctrine, generating timely, accurate, and exploitable geospatial products from tactical platforms is a critical capability to meet threats. The US Army Corps of Engineers, Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL) is carrying out 6.2 research to facilitate the creation of three-dimensional (3D) products from tactical sensors to include full-motion video, framing cameras, and sensors integrated on small Unmanned Aerial Systems (sUAS). This report describes an ERDC-GRL processing pipeline comprising custom code, open-source software, and commercial off-the-shelf (COTS) tools to geospatially rectify tactical imagery to authoritative foundation sources. Four datasets from different sensors and locations were processed against National Geospatial-Intelligence Agency–supplied foundation data. Results showed that the co-registration of tactical drone data to reference foundation varied from 0.34 m to 0.75 m, exceeding the accuracy objective of 1 m described in briefings presented to Army Futures Command (AFC) and the Assistant Security of the Army for Acquisition, Logistics and Technology (ASA(ALT)). A discussion summarizes the results, describes steps to address processing gaps, and considers future efforts to optimize the pipeline for generation of geospatial data for specific end-user devices and tactical applications.

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