Relevant bibliographies by topics / Image collection

Contents

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

Academic literature on the topic 'Image collection'

Author: Grafiati
Published: 9 March 2023
Last updated: 22 June 2025

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Journal articles on the topic "Image collection"

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Riahi Samani, Zahra, and Mohsen Ebrahimi Moghaddam. "Image Collection Summarization Method Based on Semantic Hierarchies." AI 1, no. 2 (2020): 209–28. http://dx.doi.org/10.3390/ai1020014.

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The size of internet image collections is increasing drastically. As a result, new techniques are required to facilitate users in browsing, navigation, and summarization of these large volume collections. Image collection summarization methods present users with a set of exemplar images as the most representative ones from the initial image collection. In this study, an image collection summarization technique was introduced according to semantic hierarchies among them. In the proposed approach, images were mapped to the nodes of a pre-defined domain ontology. In this way, a semantic hierarchical classifier was used, which finally mapped images to different nodes of the ontology. We made a compromise between the degree of freedom of the classifier and the goodness of the summarization method. The summarization was done using a group of high-level features that provided a semantic measurement of information in images. Experimental outcomes indicated that the introduced image collection summarization method outperformed the recent techniques for the summarization of image collections.
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Guo, Feng Ying. "The Hardware Design and Implement of an Image Information Collection System." Advanced Materials Research 804 (September 2013): 211–15. http://dx.doi.org/10.4028/www.scientific.net/amr.804.211.

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It introduces the hardware design and implement of the image information collection system which is one part of Fluorescent magnetic particle nondestructive detection system of Cannonball. The image information collection system includes Open collecting card model Initialize collection card modelApply for EMS memory modelCollecting image modelWrite bitmap information head model Show pictures modeClose collection card model. Through collecting image information to the EMS memory and then processing the image information, the magnetic images on the cannonball are showed clearly on computer, and cracks on the cannonball can easily to be judged. The software of the image information collection system is developed by Visual C++.
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Kim, Namhoon, Eunha Chun, and Eunju Ko. "Country of origin effects on brand image, brand evaluation, and purchase intention." International Marketing Review 34, no. 2 (2017): 254–71. http://dx.doi.org/10.1108/imr-03-2015-0071.

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Purpose The purpose of this paper is to analyze how national stereotype, country of origin (COO), and fashion brand’s images influence consumers’ brand evaluations and purchase intentions regarding fashion collections. Korea (Seoul) and overseas (New York and Paris) collections are compared and analyzed. Design/methodology/approach The authors conduct a structural equation modeling and multi-group analysis using data collected from Seoul, New York, and Paris. Findings Consumers make higher brand evaluations and ultimately have stronger purchase intentions toward fashion collections from countries that have stronger COO and fashion brand images. In the context of fashion collections, COO image is greatly influenced by a nation’s political economic and cultural artistic images. In addition, comparing the domestic Seoul fashion collection with New York and Paris collections reveals that a national stereotype images, COO images of fashion collection, and fashion brand’s images cause different brand evaluation and purchase intention. Originality/value The overarching value of the study is that it expands COO research, which has been limited to actual products. Also, the results provide a basic foundation for establishing marketing strategy based on COO image as a way to enhance the development and image of fashion collection.
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Blatter, Jeremy. "Wellcome Library Moving Image and Sound Collection, (http://wellcomelibrary.org/about-us/about-the-collections/moving-image-and-sound-collection/)." Medical History 57, no. 3 (2013): 459–60. http://dx.doi.org/10.1017/mdh.2013.29.

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Groom, Quentin, Mathias Dillen, Wouter Addink, et al. "Envisaging a global infrastructure to exploit the potential of digitised collections." Biodiversity Data Journal 11 (November 30, 2023): e109439. https://doi.org/10.3897/BDJ.11.e109439.

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Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in.
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Caspers, Max. "Image Recognition to Enhance the Value of Collections." Biodiversity Information Science and Standards 2 (June 13, 2018): e26320. http://dx.doi.org/10.3897/biss.2.26320.

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Techniques for image recognition through machine learning have advanced rapidly over recent years and applications using this technique are becoming increasingly common.. Applications using image recognition have enormous potential not only for research, education, conservation and capacity-building but certainly also for collections management. Perhaps by now an even bigger challenge than the technological one is supplying content in the form of large amounts of validated images. With an estimated 44 million objects, the collection of Naturalis Biodiversity Center has plenty of physical source material. During a five-year digitization programme (2010–2015) at Naturalis, 4.4 million herbarium sheets were imaged and since the start of the “Butterflies in Bags” project, 50,000 papered butterflies (out of more than 500,000) have been digitized and photographed by volunteers in a standardized manner. Still there are large parts of our collection that are not digitized at specimen level, let alone imaged, but hold great potential for collections work. This poster presents a workflow for efficient scanning of insect drawers and automated segmentation of those images to “feed” deep learning-based image recognition with images of individual insects. It will also demonstrate how this will aid in enhancing the value of our collections. With proper expert validation early on in the process, the software could mature and become more independent in such a way that ultimately, it could be used by non-specialist professionals to identify the majority of common species. The technique would pinpoint anomalies based on self-learned patterns, both in unidentified and in already identified specimens, and link those back to the taxonomic specialist. Not only does image recognition aid taxonomy, it may also hold potential for conservation and management by, for example, detecting damaged specimens or managing space utilization of drawers.
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Caspers, Max. "Image Recognition to Enhance the Value of Collections." Biodiversity Information Science and Standards 2 (June 13, 2018): e26320. https://doi.org/10.3897/biss.2.26320.

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Techniques for image recognition through <i>machine learning</i> have advanced rapidly over recent years and applications using this technique are becoming increasingly common.. Applications using image recognition have enormous potential not only for research, education, conservation and capacity-building but certainly also for collections management. Perhaps by now an even bigger challenge than the technological one is supplying content in the form of large amounts of validated images. With an estimated 44 million objects, the collection of Naturalis Biodiversity Center has plenty of physical source material. During a five-year digitization programme (2010–2015) at Naturalis, 4.4 million herbarium sheets were imaged and since the start of the "Butterflies in Bags" project, 50,000 papered butterflies (out of more than 500,000) have been digitized and photographed by volunteers in a standardized manner. Still there are large parts of our collection that are not digitized at specimen level, let alone imaged, but hold great potential for collections work. This poster presents a workflow for efficient scanning of insect drawers and automated segmentation of those images to "feed" deep learning-based image recognition with images of individual insects. It will also demonstrate how this will aid in enhancing the value of our collections. With proper expert validation early on in the process, the software could mature and become more independent in such a way that ultimately, it could be used by non-specialist professionals to identify the majority of common species. The technique would pinpoint anomalies based on self-learned patterns, both in unidentified and in already identified specimens, and link those back to the taxonomic specialist. Not only does image recognition aid taxonomy, it may also hold potential for conservation and management by, for example, detecting damaged specimens or managing space utilization of drawers.
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Martin, William. "Satellite image collection optimization." Optical Engineering 41, no. 9 (2002): 2083. http://dx.doi.org/10.1117/1.1495856.

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Legland, David, and Marie-Françoise Devaux. "ImageM: a user-friendly interface for the processing of multi-dimensional images with Matlab." F1000Research 10 (April 30, 2021): 333. http://dx.doi.org/10.12688/f1000research.51732.1.

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Modern imaging devices provide a wealth of data often organized as images with many dimensions, such as 2D/3D, time and channel. Matlab is an efficient software solution for image processing, but it lacks many features facilitating the interactive interpretation of image data, such as a user-friendly image visualization, or the management of image meta-data (e.g. spatial calibration), thus limiting its application to bio-image analysis. The ImageM application proposes an integrated user interface that facilitates the processing and the analysis of multi-dimensional images within the Matlab environment. It provides a user-friendly visualization of multi-dimensional images, a collection of image processing algorithms and methods for analysis of images, the management of spatial calibration, and facilities for the analysis of multi-variate images. ImageM can also be run on the open source alternative software to Matlab, Octave. ImageM is freely distributed on GitHub: https://github.com/mattools/ImageM.
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Turner, J. N., D. H. Szarowski, B. Roysam, and T. J. Holmes. "Light Microscopy Image Collection: Confocal, Widefield and Deconvolution." Microscopy and Microanalysis 3, S2 (1997): 371–72. http://dx.doi.org/10.1017/s1431927600008746.

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Light microscopy instrumentation and biological applications continue to expand rapidly, and an important aspect of this expansion is three-dimensional (3-D) imaging and image analysis. For many biological specimens, optical sectioning, i.e. collecting images at a sequence of depths under controlled conditions, provides true 3-D data through the entire specimen. This is especially important for specimens whose thickness exceeds the depth-of-field of the microscope objective lens. This sequence of optical sections is the basis for 3-D image reconstruction providing information from all three specimen dimensions instead of just the traditional two in the image plane of the microscope. The analysis of images in 3-D provides insights into the structure and function of biological specimens that are not available through other means. However, 3-D microscopy also presents additional choices for image collection. The first of which is whether to use widefield or confocal microscopy and the second is whether to utilize digital deblurring or deconvolution methods.
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Dissertations / Theses on the topic "Image collection"

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GRECO, Luca. "AUTOMATIC ORGANIZATION OF MULTIMEDIA DATA COLLECTIONS." Doctoral thesis, Università degli Studi di Palermo, 2014. http://hdl.handle.net/10447/91234.

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La fotografia digitale ha avuto uno sviluppo sempre crescente negli ultimi dieci anni. Prima la diminuzione dei prezzi delle apparecchiature di acquisizione e poi l’integrazione di queste nei dispositivi portatili di uso quotidiano (i.e. smartphone, tablet) ha permesso a chiunque di potere creare e conservare semplicemente un enorme numero di immagini. Inoltre l’immagine stessa é diventata uno strumento di comunicazione, portando alla nascita di social networks basati unicamente sulla condivisione di fotografie (flickr, instagram, etc...). La gestione di tali quantitá di dati é quindi diventato un problema reale per molti utenti, in quanto il ritrovamento e l’organizzazione di questi dati é un compito dispendioso dal punto di vista del tempo e di difficile integrazione con immagini archiviate nel passato in modo non organizzato. Questa tesi si pone come obiettivo quello di illustrare le problematiche collegate alla organizzazione di collezioni di immagini che rappresentano eventi reali ed alla fusione tra collezioni che riguardano lo stesso evento ma che provengono da sorgenti diverse. Per effettuare una organizzazione delle collezioni é necessario innanzitutto definire una struttura degli eventi: i metodi proposti presuppongono che ogni evento non sia un blocco unitario di immagini ma che sia costituito da un numero di sotto-elementi distinguibili per la loro collocazione temporale o per il loro contenuto visivo. Alcune tecniche dello stato dell’arte illustrate in questo lavoro hanno fornito degli strumenti utili per effettuare raggruppamenti di immagini, in special modo dal punto di vista temporale. Anche dal punto di vista del contenuto sono stati proposti diversi metodi di descrizione delle immagini, analizzando caratteristiche globali, quali il colore e la sua distribuzione, o puntuali cercando di individuare e descrivere punti caratteristici per ogni immagine. L’ultima parte di questa tesi si basa su alcune possibili elaborazioni che si pos- sono effettuare sulle collezioni ordinate o sul risultato della fusione di collezioni differenti. Il primo metodo proposto affronta il problema dell’individuazione di soggetti all’interno delle immagini e della creazione di anteprime per la facilitazione del reperimento delle stesse o per la loro presentazione. Un secondo metodo pro- posto é focalizzato sul taglio estetico delle stesse usando un algoritmo dal basso costo computazionale che senza tenerle esplicitamente in conto rispetta le regole classiche della composizione fotografica. Il resto delle applicazioni invece é orientato al ritrovamento di oggetti personali all’interno delle collezioni. Una delle applicazioni usa un database di oggetti conosciuti composto per ognuno di questi da una successione di viste ruotando lo stesso di uno scarto costante. La seconda applicazione, invece, é basata su un database di video di oggetti che ruotano uniformemente e permette di effettuare query usando dei video di costruzione simile.<br>The technological development of digital photography is ever increasing in last ten years. The decreasing costs of the acquisition devices and the integration in commonly used mobile devices (i.e. smartphones, tablets) has given to the mayority of users the possibility to create and store a very large number of images. Furthermore, the image itself has become a communication item leading to the creation of social networks totally based on picture sharing (Flickr, Instagram and so on). Managing this huge amount of data today is a real problem for many users be- cause the retrieval and the organization of these is an annoyng and time-consuming task, difficult to integrate with images stored in the past without a fixed organi- zation. The aim of this thesis is to show the issues related to the problem of managing image collections that represent real events and merging collections regarding the same event but from different sources. To make an organization of the collections it is necassary to define a structure for the events: proposed methods assume that an event is not a single block of images but is composed by a set of sub-events that can be distinguished by using temporal information or visual content. Some of the techniques of the state of the art described in this thesis provided some useful tools to cluster images, especially using the time as basis. Others use visual information to describe images, analyzing global features like color and its distribution or local features, trying to detect and describe intresting points for each image. The last part of this thesis is based on some possible elaboration on the or- dered collections or on the result of different collections fusion. The first proposed method is focused on the problem of subjects extraction in images and in thumb- nails creation to facilitate retrieval and browsing. A second method performs an aesthetical cut on images using a low computational cost algorithm that respects the common rules of photography composition without taking them into account explicitally. The remainder of the applications is oriented to personal objects retrieval in collections. One of the applications uses a multiview database of known objects. The second is based on a database of videos of uniformly rotating objects and the query are done using video with a similar construction.
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Chang, Michelle T. "Collection understanding." Thesis, Texas A&M University, 2003. http://hdl.handle.net/1969.1/69.

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Collection understanding shifts the traditional focus of retrieval in large collections from locating specific artifacts to gaining a comprehensive view of the collection. Visualization tools are critical to the process of efficient collection understanding. By presenting simple visual interfaces and intuitive methods of interacting with a collection, users come to understand the essence of the collection by focusing on the artifacts. This thesis discusses a practical approach for enhancing collection understanding in image collections.
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Loisant, Erwan. "Browsing a Classification of an Image Collection." Phd thesis, Université de Nantes, 2005. http://tel.archives-ouvertes.fr/tel-00465952.

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Les données dites multimédia (images, vidéos) se distinguent des données classique par une densité variable d'information et l'impossibilité de normaliser ces données. Du fait de ces particularités, de nouvelles techniques d'indexation et de recherche d'information ont du être etudiées. Il y a principalement deux problèmes a résoudre pour la recherche d'information dans les collections multimédia (ou les bases de données multimédia) : (1) la représentation des données et (2) le processus de recherche du point de vue de l'utilisateur. Dans le cas des bases de données, l'indexation est fortement liée a ces deux problèmes. Dans le cas particulier des images, on distingue trois grandes classes: – la recherche par requêtes formelles, héritée des bases de données classiques ; – la recherche avec boucle de retour, où l'utilisateur fait partie intégrante du processus de recherche ; – la navigation où les images sont organisées en une structure preparée à l'avance, utilisée comme index et comme structure de recherche. C'est sur cette troisième approche que nos travaux se sont portés ; nous nous sommes en effet interessés au treillis de Galois, une structure de graphe permettant d'organiser les éléments d'une relation binaire. Une telle structure de navigation a plusieurs avantages sur une approche classique basée sur des requêtes : en particulier, elle permet d'affranchir l'utilisateur d'une phase de rédaction de requête.
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LEONARDI, MARCO. "Image Collection Management using Convolutional Neural Networks." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/365014.

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Al giorno d’oggi ormai quasi chiunque possiede uno smartphone dotato di una telecamera ad alta risoluzione. Negli ultimi decenni, i contenuti multimediali (immagini e video) stanno sempre più spesso diventando il principale mezzo di comunicazione. Dato il continuo calo dei prezzi dei dispositivi di archiviazione, il numero totale di immagini salvate sta aumentando notevolmente, andando così a creare collezioni di immagini sempre più grandi, a tal punto da essere una problema per chi vuole le vuole esplorare. Data una libreria di immagini, il processo di selezione di un gruppo di foto che rappresenti al meglio le informazioni contenute in essa è condizionato dalle proprietà percettive delle immagini. Al fine di gestire in modo automatico questa selezione, in letteratura sono stati proposti diversi metodi che sfruttano le proprietà percettive delle immagini. Questi metodi hanno come scopo quello di associare alle immagini un valore numerico che ne rappresenta la presenza o meno di queste proprietà, come ad esempio la qualità, l'estetica o la memorabilità, per poi sfruttarle per selezionare le immagini migliori. La presente tesi comincia trattando quelle che sono le proprietà delle immagini fondamentali al processo di selezione delle immagini, rispettivamente la qualità e l’estetica delle immagini. Per prima cosa viene studiata la qualità delle immagini mediante un processo di rilevamento delle anomalie. Questo perché dal punto di vista di un sistema automatico di selezione delle immagini, è più indicato un metodo che sia in grado di distinguere le immagini belle da quelle brutte, piuttosto che un metodo che predica un valore ben correlato con la qualità delle immagini. Successivamente l’attenzione viene spostata sul problema della valutazione automatica dell’estetica delle immagini. In particolare viene prima proposto un metodo in grado di stimare il grado di bellezza di un'immagine a partire dalla predizione di attributi correlati all’estetica. Successivamente introducendo un metodo per la valutazione automatica dell’estetica fondato su molteplici aspetti delle immagini quali il contenuto semantico, lo stile artistico e lo stile di composizione. Uno dei tanti motivi per cui si scatta una foto è quello di poter essere poi in grado di rivivere il momento impresso semplicemente riguardando la foto. Le immagini possono essere pertanto viste come un collegamento concreto tra i propri ricordi e gli eventi passati. La memorabilità delle immagini è pertanto una proprietà fondamentale nell’organizzazione delle immagini. Essere in grado di riconoscere queste immagini memorabili, significa poter favorire la loro selezione. Per questo motivo nella suddetta tesi viene presentato un metodo capace di stimare la memorabilità delle immagini. In particolare la soluzione proposta va nella direzione di predire la memorabilità delle immagini scomponendo le proprietà intrinseche delle immagini che influenzano la memorabilità. Per finire, considerando che le collezioni di immagini tendono spesso ad avere molteplici foto simili tra loro. Al fine di garantire una selezione di immagini il più diversa e rappresentativa possibile, viene proposto un metodo flessibile ed innovativo per riassumere automaticamente le collezioni di immagini. A tal proposito, il metodo introdotto è stato progettato considerando diversi aspetti delle immagini tra cui la categoria della scena, la qualità e l'estetica.<br>Almost everyone carries a high-quality camera in their smartphone and uses it to communicate with other individuals and for the last two decades, people are increasingly making use of images and videos in their transportable communication. As the prices of the storage are decreasing, the number of photos stored is increasing, leading to collections of images whose sizes begin to be a barrier for relieving the captured moments and exploring them. We are submerged by images. In order to ease the problem of oversized image collections, methods that aim to select a subset of photos that best represents them have been designed and proposed in the literature. Those methods typically rely upon the prediction of perceptual features such as, for example, the image quality, aesthetics, and memorability, to select the best images. This thesis starts from the fundamental image properties that guide the image selection, respectively the image quality and image aesthetics. First, the perceived image quality assessment is investigated in an anomaly detection manner, contrary to the most common regression task. This is because rather than predict a score that best correlates to the average human opinion, being able to distinguish good quality images from bad ones, is more suitable for the image collection management problem, furthermore, it requires fewer images to tune the model. Then the problem of automatic assessment of image aesthetics is introduced. In the beginning, presenting a method that learns the aesthetics of a picture on the basis of the prediction of aesthetics-related attributes. Then, a new solution that takes into account the semantic content, the artistic style, and the composition of the image is presented. One of the reasons people take photos is to capture important situations to recall them later on, usually with the intention of afterwards sharing their photos with other people like friends or family members. Photos can be seen as a concrete link between our memories and experienced events. Image memorability can be helpful in the organization of the selected images to better bind the memory of experienced events and the taken images. To this end in this thesis, a method for the estimation of still image memorability is presented. In particular, the proposed method goes in the direction of breaking down the intrinsic image properties that influence the memorability of the pictures. Image collections tend to have several similar images. This is because to ensure the best shot, people usually take a series of photos of the same scene. To guarantee a diverse and representative selection of images from a large collection, this thesis concludes by proposing a flexible and innovative framework that can be used to both explore large-scale image datasets and to summarize photo albums. The proposed method is designed to exploit different aspects of the images, such as the scene category, image quality, and image aesthetics.
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Torok, Matthew M. "Autonomous Sample Collection Using Image-Based 3D Reconstructions." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/32163.

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Sample collection is a common task for mobile robots and there are a variety of manipulators available to perform this operation. This thesis presents a novel scoop sample collection system design which is able to both collect and contain a sample using the same hardware. To ease the operator burden during sampling the scoop system is paired with new semi-autonomous and fully autonomous collection techniques. These are derived from data provided by colored 3D point clouds produced via image-based 3D reconstructions. A custom robotic mobility platform, the Scoopbot, is introduced to perform completely automated imaging of the sampling area and also to pick up the desired sample. The Scoopbot is wirelessly controlled by a base station computer which runs software to create and analyze the 3D point cloud models. Relevant sample parameters, such as dimensions and volume, are calculated from the reconstruction and reported to the operator. During tests of the system in full (48 images) and fast (6-8 images) modes the Scoopbot was able to identify and retrieve a sample without any human intervention. Finally, a new building crack detection algorithm (CDA) is created to use the 3D point cloud outputs from image sets gathered by a mobile robot. The CDA was shown to successfully identify and color-code several cracks in a full-scale concrete building element.<br>Master of Science
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Dyer, Emily L. "Sugar nine : a collection of short stories /." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2308.pdf.

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Buenrostro-Nava, Marco T. "Characterization of GFP Gene Expression Using an Automated Image Collection System and Image Analysis." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1032794680.

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Christiansen, Naomi Lund. "Learning to Create: A Collection of Personal Essays." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd485.pdf.

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Lloyd, Jana. "Finding Where I Am: A Collection of Creative Nonfiction - Creative thesis." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd771.pdf.

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Watson, Myles G. "Does the Halting Necessary for Hardware Trace Collection Inordinately Perturb the Results?" Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd594.pdf.

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Books on the topic "Image collection"

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National Geographic Society (U.S.), ed. National Geographic Image Collection. Focal Point, 2009.

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Belgium) Musée de la photographie (Charleroi. Image(s) d'une collection. Musée de la Photographie à Charleroi & Fonds Mercato, 2010.

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S, Philip Neil, and National Geographic Society (U.S.), eds. National Geographic image collection. [National Geographic Society, 1997.

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Musée de Grenoble. Image d'une collection: Musée de Grenoble. Réunion des musées nationaux, 1999.

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1940-, Jule Walter, ed. Sightlines: Printmaking and image culture : a collection of essays and images. University of Alberta Press, 1997.

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Nina, Felshin, Phoenix Art Museum, and Art Museum Association of America., eds. Focus on the image: Selections from the Rivendell Collection. s.n.], 1985.

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IMSI. Masterclips 303,000: Award-winning premium image collection. IMSI, 1998.

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Technology, Rochester Institute of, ed. Cary Collection: Graphic arts library & digital image database. RIT, Cary Graphic Arts Press, 1993.

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Bayle, Francois. L' Image, l'argent, les titres: Valeurs de collection. Editions de l'Epargne, 1987.

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1966-, White Shawna, Williamson Karen 1967-, Adamowicz-Clements Sharona, and McMichael Canadian Art Collection, eds. The Arctic image. McMichael Canadian Art Collection, 2004.

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Book chapters on the topic "Image collection"

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Hibbs, Alan R. "Image Collection." In Confocal Microscopy for Biologists. Springer US, 2004. http://dx.doi.org/10.1007/978-0-306-48565-7_4.

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Taslakian, Bedros. "Aspiration of Abdominopelvic Fluid Collection." In Procedural Dictations in Image-Guided Intervention. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40845-3_65.

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Koeva, Svetla. "Multilingual Image Corpus." In European Language Grid. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17258-8_22.

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AbstractThe ELG pilot project Multilingual Image Corpus (MIC 21) provides a large image dataset with annotated objects and multilingual descriptions in 25 languages. Our main contributions are: the provision of a large collection of highquality, copyright-free images; the formulation of an ontology of visual objects based on WordNet noun hierarchies; precise manual correction of automatic image segmentation and annotation of object classes; and association of objects and images with extended multilingual descriptions. The dataset is designed for image classification, object detection and semantic segmentation. It can be also used for multilingual image caption generation, image-to-text alignment and automatic question answering for images and videos.
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Berretti, S., A. Del Bimbo, and P. Pala. "Collection Fusion for Distributed Image Retrieval." In Distributed Multimedia Information Retrieval. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24610-7_6.

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Worring, Marcel. "Multimedia Analytics for Image Collection Forensics." In Handbook of Digital Forensics of Multimedia Data and Devices. John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118705773.ch8.

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Molnár, P., and T. R. Collins. "Traffic Data Collection Using Image Processing Technology." In Traffic and Granular Flow ’99. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59751-0_35.

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Rochow, Theodore George, and Paul Arthur Tucker. "Image Collection, Analysis, and Reconstruction by Computer." In Introduction to Microscopy by Means of Light, Electrons, X Rays, or Acoustics. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1513-9_19.

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Song, Mofei, Zhengxing Sun, Bo Li, and Jiagao Hu. "Iterative Active Classification of Large Image Collection." In MultiMedia Modeling. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73603-7_24.

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Singh, Anurag, and Deepak Kumar Sharma. "Image Collection Summarization: Past, Present and Future." In Data Visualization and Knowledge Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25797-2_3.

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Waltner, Georg, Malte Jaschik, Alfred Rinnhofer, Horst Possegger, and Horst Bischof. "An Intelligent Scanning Vehicle for Waste Collection Monitoring." In Image Analysis and Processing – ICIAP 2022. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06427-2_4.

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Conference papers on the topic "Image collection"

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Hou, Xinlong, Xueshen Li, Nirupama Ravi, Ziyi Huang, and Yu Gan. "Reinforcement-learning-based proactive medical dialogue system for health status and medical image collection." In Image Processing, edited by Olivier Colliot and Jhimli Mitra. SPIE, 2025. https://doi.org/10.1117/12.3047535.

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Gershbock, Richard. "Image acquisition: quality control for document image scanners." In Critical Review Collection. SPIE, 1991. http://dx.doi.org/10.1117/12.48889.

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Tajahuerce, Enrique, and Bahram Javidi. "Three-dimensional image security." In Critical Review Collection. SPIE, 2001. http://dx.doi.org/10.1117/12.419787.

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Buczynski, Ryszard, Tomasz Szoplik, Irina P. Veretennicoff, and Hugo Thienpont. "Photonic morphological image processing." In Critical Review Collection. SPIE, 2001. http://dx.doi.org/10.1117/12.449677.

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Sandrik, John M. "Standardization of image quality measurements of medical x-ray image intensifier systems." In Critical Review Collection. SPIE, 1991. http://dx.doi.org/10.1117/12.48897.

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Urban, Stephen. "Survey of standards for image telecommunications." In Critical Review Collection. SPIE, 1996. http://dx.doi.org/10.1117/12.229254.

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Psaltis, Demetri, Yong Qiao, and Sergei S. Orlov. "Adaptive optical networks for image recognition." In Critical Review Collection. SPIE, 1994. http://dx.doi.org/10.1117/12.178617.

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Tajahuerce, Enrique, Osamu Matoba, Yann Frauel, Maria-Albertina Castro, and Bahram Javidi. "New approaches to 3D image recognition." In Critical Review Collection. SPIE, 2001. http://dx.doi.org/10.1117/12.449689.

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Sheng, Yunlong, Xiangjie Yang, Daniel McReynolds, Pierre Valin, and Leandre Sevigny. "Multisensor image registration and optical correlation." In Critical Review Collection. SPIE, 1999. http://dx.doi.org/10.1117/12.365906.

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Vahey, Michael, and Robert F. Cody. "Parallel processing architectures for image processing systems." In Critical Review Collection. SPIE, 1995. http://dx.doi.org/10.1117/12.204205.

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Reports on the topic "Image collection"

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Yeum, Chul Min, Anup Mohan, Shirley J. Dyke, et al. Image-Based Collection and Measurements for Construction Pay Items. Purdue University, 2017. http://dx.doi.org/10.5703/1288284316510.

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Tuozzolo S. Camera Assembly design proposal for SRF cavity image collection. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1061984.

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Tuozzolo, S. Camera assembly design proposal for SRF cavity image collection. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1029586.

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Gignac, Paul, Sarah Wright, Mariah Kenney, Amy Schuler, and Neggin Keshavarzian. Scientific Images Curation Curriculum. University of Minnesota Libraries, 2024. http://dx.doi.org/10.24926/2024.265766.

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A collection of materials used to instruct individuals how to curate scientific images. This is primarily targeted towards data stewards, but can be used by any and all when instructing on scientific image curation.
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Ngan, Mei, George W. Quinn, and Patrick Grother. Tattoo Recognition Technology – Best Practices (Tatt-BP) Guidelines for Tattoo Image Collection. National Institute of Standards and Technology, 2016. http://dx.doi.org/10.6028/nist.ir.8109.

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Alshaibi, Omar, Victoria Armstrong, Katie Brown, et al. Images of Research: An Art Gallery and Puzzle Book. Edited by Sandra Oza. University of Dundee, 2024. http://dx.doi.org/10.20933/100001304.

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Images of Research is an annual competition that challenges researchers to capture their work in a single image, alongside a short description. This competition has been run at the University of Dundee since 2020 and represents just a handful of the research projects being carried out by postgraduate researchers. The competition celebrates our research and the many original ways it can be expressed. This collection showcases the winning entries, mixed with fun sketches and puzzles to complete.
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Petrie, G. M., E. M. Perry, R. R. Kirkham, and D. E. Slator. Advanced image collection, information extraction, and change detection in support of NN-20 broad area search and analysis. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/552798.

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Heger, Karl, and Lasse Petersen. Tomato (software). GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany, 2024. http://dx.doi.org/10.3289/sw_5_2024.

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The Tomato Tools are a collection of graphical user interface applications related to the Acquisition, Curation and Management Workflow of marine image data. The tools can be used as standalone applications or in conjunction to form whole workflows. For the latter the launcher Tomato provides an interface to create, manage and execute such workflows.
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Bhatt, Parth, Curtis Edson, and Ann MacLean. Image Processing in Dense Forest Areas using Unmanned Aerial System (UAS). Michigan Technological University, 2022. http://dx.doi.org/10.37099/mtu.dc.michigantech-p/16366.

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Imagery collected via Unmanned Aerial System (UAS) platforms has become popular in recent years due to improvements in a Digital Single-Lens Reflex (DSLR) camera (centimeter and sub-centimeter), lower operation costs as compared to human piloted aircraft, and the ability to collect data over areas with limited ground access. Many different application (e.g., forestry, agriculture, geology, archaeology) are already using and utilizing the advantages of UAS data. Although, there are numerous UAS image processing workflows, for each application the approach can be different. In this study, we developed a processing workflow of UAS imagery collected in a dense forest (e.g., coniferous/deciduous forest and contiguous wetlands) area allowing users to process large datasets with acceptable mosaicking and georeferencing errors. Imagery was acquired with near-infrared (NIR) and red, green, blue (RGB) cameras with no ground control points. Image quality of two different UAS collection platforms were observed. Agisoft Metashape, a photogrammetric suite, which uses SfM (Structure from Motion) techniques, was used to process the imagery. The results showed that an UAS having a consumer grade Global Navigation Satellite System (GNSS) onboard had better image alignment than an UAS with lower quality GNSS.
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Stelmakh, Marta. HISTORICAL CONTEXT IN THE COLLECTION OF ARTICLES BY TIMOTHY SNYDER «UKRAINIAN HISTORY, RUSSIAN POLITICS, EUROPEAN FUTURE». Ivan Franko National University of Lviv, 2021. http://dx.doi.org/10.30970/vjo.2021.50.11098.

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The article examines the problem of the image formation of Ukraine in the international arena in the historical journalism of Timothy Snyder. The subject of the research is the historical context in the journalistic collection «Ukrainian History, Russian Politics, European Future». It identifies the main considerations of the author on the past of Russian-Ukrainian relations and the need to develop historical consciousness in the fight against Russian manipulation. Methodology: the comparative, historical, system analysis and other methods are used in the process of scientific research. The results of the study were obtained by analysing the author’s journalistic works and by considering the main historical themes raised by Timothy Snyder. Main results: The historical context in Timothy Snyder’s journalism is often focused on the Holodomor and the events of World War II. After all, these events are connected with the beginning of the image formation of the Ukrainian people as supporters of Nazism by the Russian authorities and the devaluation of the Ukrainians’ contribution to the establishment of peace during the Second World War. It is determined that the non-reflective attitude to history, the inability to draw parallels between the events of the past and the future leads to an ineffective response to manipulation and propaganda, which can threaten world peace. Conclusions: the realization that Russian aggression against Ukraine has its own history is a necessary aspect in the elucidation of this issue. The Eurasian Union and cooperation with the European far-right are Russian propaganda tools that discredit the Ukrainian state in the world community. Publicist Timothy Snyder points out that Europe’s future interconnects with the past, so he emphasizes the need to study and rethink history, which today has become the object of propaganda and manipulation. Significance: The results of our study will help journalists who study the historical aspect of journalistic materials and research foreign materials on Ukrainian issues. In addition, our research is necessary for Ukraine, because Russia’s aggression continues, as well as the aggressor’s propaganda, which is based on the distortion and falsification of historical events.
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