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1

Iwaszczuk, D., and U. Stilla. "QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 3–8. http://dx.doi.org/10.5194/isprsannals-iii-1-3-2016.

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Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.
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Iwaszczuk, D., and U. Stilla. "QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 3–8. http://dx.doi.org/10.5194/isprs-annals-iii-1-3-2016.

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Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.
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Paradis, V. "Analyse proteomique et imagerie moleculaire." Journal de Radiologie 89, no. 10 (October 2008): 1290. http://dx.doi.org/10.1016/s0221-0363(08)75848-7.

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4

Li, Yu, Jun Liu, Ke-feng Ji, and Yi Su. "Texture Feature Extraction and Analyses for Mobile Targets in High-Resolution SAR Imagery." Journal of Electronics & Information Technology 30, no. 12 (April 25, 2011): 2809–12. http://dx.doi.org/10.3724/sp.j.1146.2007.01059.

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5

Taourel, P., and G. Laffargue. "Analyse de livre - Cas cliniques en imagerie urologique et gynécologique." Imagerie de la Femme 16, no. 2 (June 2006): 143. http://dx.doi.org/10.1016/s1776-9817(06)77534-4.

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Leclerc, X., J. Y. Gauvrit, J. F. Meder, and J. P. Pruvo. "Imagerie radiologique des sténoses carotidiennes asymptomatiques : quand ? Comment ? Analyse critique." Annales de Cardiologie et d'Angéiologie 53, no. 1 (January 2004): 4–11. http://dx.doi.org/10.1016/j.ancard.2003.11.003.

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Guyot, Adrien, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan. "Segmentation of polarimetric radar imagery using statistical texture." Atmospheric Measurement Techniques 16, no. 19 (October 12, 2023): 4571–88. http://dx.doi.org/10.5194/amt-16-4571-2023.

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Abstract. Weather radars are increasingly being used to study the interaction between wildfires and the atmosphere, owing to the enhanced spatio-temporal resolution of radar data compared to conventional measurements, such as satellite imagery and in situ sensing. An important requirement for the continued proliferation of radar data for this application is the automatic identification of fire-generated particle returns (pyrometeors) from a scene containing a diverse range of echo sources, including clear air, ground and sea clutter, and precipitation. The classification of such particles is a challenging problem for common image segmentation approaches (e.g. fuzzy logic or unsupervised machine learning) due to the strong overlap in radar variable distributions between each echo type. Here, we propose the following two-step method to address these challenges: (1) the introduction of secondary, texture-based fields, calculated using statistical properties of gray-level co-occurrence matrices (GLCMs), and (2) a Gaussian mixture model (GMM), used to classify echo sources by combining radar variables with texture-based fields from (1). Importantly, we retain all information from the original measurements by performing calculations in the radar's native spherical coordinate system and introduce a range-varying-window methodology for our GLCM calculations to avoid range-dependent biases. We show that our method can accurately classify pyrometeors' plumes, clear air, sea clutter, and precipitation using radar data from recent wildfire events in Australia and find that the contrast of the radar correlation coefficient is the most skilful variable for the classification. The technique we propose enables the automated detection of pyrometeors' plumes from operational weather radar networks, which may be used by fire agencies for emergency management purposes or by scientists for case study analyses or historical-event identification.
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Zullino, Daniele, Gerard Calzada, Julie Gaspoz, Sophia Achab, and Gabriel Thorens. "La neurotoxicité du cannabis : analyse des données de neuro-imagerie structurelle." Psychotropes 23, no. 2 (2017): 111. http://dx.doi.org/10.3917/psyt.232.0111.

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9

Pruvo, J. P., J. P. Pierme, J. P. Beregi, A. Cotten, O. Ernst, L. Lemaitre, and M. Remy-Jardin. "Analyse des activites merri migac en imagerie au chru de lille." Journal de Radiologie 87, no. 10 (October 2006): 1261. http://dx.doi.org/10.1016/s0221-0363(06)86908-8.

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10

Jardri, R. "Imagerie multimodale de l’état hallucinatoire." European Psychiatry 29, S3 (November 2014): 554. http://dx.doi.org/10.1016/j.eurpsy.2014.09.354.

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ContexteLes hallucinations figurent parmi les symptômes les plus invalidants de la schizophrénie. Même si ces expériences peuvent survenir à la fois dans la modalité auditive (HA) et visuelle (HV), l’impact de la présence d’une ou de deux modalités hallucinatoires (HA + V) reste peu exploré dans la schizophrénie. Cette étude vise donc à préciser les variations de connectivité fonctionnelle et structurale observables en fonction de la complexité hallucinatoire. Ces analyses seront complétées par des mesures structurales destinées à étudier l’impact de la plasticité et de facteurs neurodéveloppementaux sur la complexité hallucinatoire.MéthodeDeux groupes de sujets avec diagnostic de schizophrénie et souffrant tous d’HA ont été inclus et appariés sur l’âge, le genre, les scores de PANSS et les doses d’antipsychotique. Le groupe HA (n = 16) n’a jamais présenté d’hallucination visuelle, alors que le groupe HA + V (n = 17) présente des HV supplémentaires. Pour l’ensemble des analyses (connectivité fonctionnelle de repos ciblée sur l’hippocampe ou le nucleus accumbens, connectivité structurale par tract-based spatial statistics, analyse de forme et index de gyrification), une comparaison de groupe a été réalisée selon un modèle d’Ancova avec l’âge comme co-variable (qFDR < 0,05).Résultats-discussionDes différences de connectivité ont été mises en évidence sur la voie mésolimbique et entre aires visuelles et complexe hippocampique. Ces différences sont liées à la présence d’HV complémentaires et ne peut être attribuée aux facteurs schizophrénie ou HA, contrôlés par le design expérimental. La présence d’HV chez les patients souffrant de schizophrénie avec HA est également associée à des modifications plastiques de la forme de l’hippocampe et à une vulnérabilité développementale précoce (baisse de gyrification). Les futures études portant sur les hallucinations devront non seulement s’intéresser à la sévérité de ces symptômes mais aussi à leur complexité sensorielle.
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Balvay, D., N. Kachenoura, I. Thomassin-Naggara, O. Clément, and C. A. Cuénod. "Filtrage par analyse en composantes principales (ACP) adaptatif en imagerie medicale dynamique." Journal de Radiologie 90, no. 10 (October 2009): 1262. http://dx.doi.org/10.1016/s0221-0363(09)75043-7.

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Falgarone, Géraldine, Raphaël Porcher, Agnès Duché, Sami Kolta, Maxime Dougados, and Christian Roux. "Identification des patientes ostéoporotiques par analyse ultrasonore osseuse avec ou sans imagerie." Revue du Rhumatisme 71, no. 9 (October 2004): 801–6. http://dx.doi.org/10.1016/j.rhum.2003.09.019.

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13

Awuah, Kwame T., Paul Aplin, Christopher G. Marston, Ian Powell, and Izak P. J. Smit. "Probabilistic Mapping and Spatial Pattern Analysis of Grazing Lawns in Southern African Savannahs Using WorldView-3 Imagery and Machine Learning Techniques." Remote Sensing 12, no. 20 (October 15, 2020): 3357. http://dx.doi.org/10.3390/rs12203357.

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Savannah grazing lawns are a key food resource for large herbivores such as blue wildebeest (Connochaetes taurinus), hippopotamus (Hippopotamus amphibius) and white rhino (Ceratotherium simum), and impact herbivore densities, movement and recruitment rates. They also exert a strong influence on fire behaviour including frequency, intensity and spread. Thus, variation in grazing lawn cover can have a profound impact on broader savannah ecosystem dynamics. However, knowledge of their present cover and distribution is limited. Importantly, we lack a robust, broad-scale approach for detecting and monitoring grazing lawns, which is critical to enhancing understanding of the ecology of these vital grassland systems. We selected two sites in the Lower Sabie and Satara regions of Kruger National Park, South Africa with mesic and semiarid conditions, respectively. Using spectral and texture features derived from WorldView-3 imagery, we (i) parameterised and assessed the quality of Random Forest (RF), Support Vector Machines (SVM), Classification and Regression Trees (CART) and Multilayer Perceptron (MLP) models for general discrimination of plant functional types (PFTs) within a sub-area of the Lower Sabie landscape, and (ii) compared model performance for probabilistic mapping of grazing lawns in the broader Lower Sabie and Satara landscapes. Further, we used spatial metrics to analyse spatial patterns in grazing lawn distribution in both landscapes along a gradient of distance from waterbodies. All machine learning models achieved high F-scores (F1) and overall accuracy (OA) scores in general savannah PFTs classification, with RF (F1 = 95.73±0.004%, OA = 94.16±0.004%), SVM (F1 = 95.64±0.002%, OA = 94.02±0.002%) and MLP (F1 = 95.71±0.003%, OA = 94.27±0.003%) forming a cluster of the better performing models and marginally outperforming CART (F1 = 92.74±0.006%, OA = 90.93±0.003%). Grazing lawn detection accuracy followed a similar trend within the Lower Sabie landscape, with RF, SVM, MLP and CART achieving F-scores of 0.89, 0.93, 0.94 and 0.81, respectively. Transferring models to the Satara landscape however resulted in relatively lower but high grazing lawn detection accuracies across models (RF = 0.87, SVM = 0.88, MLP = 0.85 and CART = 0.75). Results from spatial pattern analysis revealed a relatively higher proportion of grazing lawn cover under semiarid savannah conditions (Satara) compared to the mesic savannah landscape (Lower Sabie). Additionally, the results show strong negative correlation between grazing lawn spatial structure (fractional cover, patch size and connectivity) and distance from waterbodies, with larger and contiguous grazing lawn patches occurring in close proximity to waterbodies in both landscapes. The proposed machine learning approach provides a novel and robust workflow for accurate and consistent landscape-scale monitoring of grazing lawns, while our findings and research outputs provide timely information critical for understanding habitat heterogeneity in southern African savannahs.
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14

Deletre, K., and AC Roudot. "Terminologie comparée français-anglais en analyse de texture." Sciences des Aliments 23, no. 3 (June 28, 2003): 463–80. http://dx.doi.org/10.3166/sda.23.463-480.

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15

Blondel, Ph, and O. Gómez Sichi. "Textural analyses of multibeam sonar imagery from Stanton Banks, Northern Ireland continental shelf." Applied Acoustics 70, no. 10 (October 2009): 1288–97. http://dx.doi.org/10.1016/j.apacoust.2008.07.015.

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16

Bertrand-Barat, Josseline, Aurélie Petit-Moneger, Anne-Sophie Parinaud, Marion Bonilla, Xavier Pineau, Marie-Pierre Loiseau-Audirac, Soazig Bohuon, et al. "Analyse des circonstances de survenue des extravasations de produits de contraste en imagerie." Santé Publique 31, no. 1 (2019): 93. http://dx.doi.org/10.3917/spub.191.0093.

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17

Zabel, J. P., T. Batch, P. Lebrun, A. Peutot, D. Chapuis, J. Lecocq, and A. Blum-Moyse. "OA13 Hypertrophie musculaire neurogene : a propos de trois cas, imagerie et meta-analyse." Journal de Radiologie 85, no. 9 (September 2004): 1538–39. http://dx.doi.org/10.1016/s0221-0363(04)77792-6.

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18

Bouchair, N., Y. Benkahoul, N. Roustila, M. Bentebbal, D. Belamri, T. Khelifi-Touhami, and M. R. Cheriet. "SFP-P004 – Imagerie et explorations – Analyse de l’activité d’une unité d’endoscopie respiratoire pédiatrique." Archives de Pédiatrie 15, no. 5 (June 2008): 946. http://dx.doi.org/10.1016/s0929-693x(08)72140-7.

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19

Kahn, E. "Imagerie spectrale et analyse de séquences d’images en microscopie confocale à balayage laser." IRBM 28, no. 3-4 (September 2007): 107–16. http://dx.doi.org/10.1016/j.rbmret.2007.07.002.

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20

Li, Yutao, Yuanhan Qin, Hui Wang, Shaodong Xu, and Shenglin Li. "Study of Texture Indicators Applied to Pavement Wear Analysis Based on 3D Image Technology." Sensors 22, no. 13 (June 30, 2022): 4955. http://dx.doi.org/10.3390/s22134955.

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Pavement texture characteristics can reflect early performance decay, skid resistance, and other information. However, most statistical texture indicators cannot express this difference. This study adopts 3D image camera equipment to collect texture data from laboratory asphalt mixture specimens and actual pavement. A pre-processing method was carried out, including data standardisation, slope correction, missing value and outlier processing, and envelope processing. Then the texture data were calculated based on texture separation, texture power spectrum, grey level co-occurrence matrix, and fractal theory to acquire six leading texture indicators and eight extended indicators. The Pearson correlation coefficient was used to analyse the correlation of different texture indicators. The distinction vector based on the information entropy is calculated to analyse the distinction of the indicators. High correlations between ENE (energy) and ENT (entropy), ENT and D (Minkowski dimension) were found. The CON (contrast) has low correlations with HT (macro-texture power spectrum area), ENT and D. However, the differentiation of ENE and HT is more prominent, and the differentiation of the CON is smaller. ENE, ENT, CON and D indicators based on macro-texture and the corresponding original texture have strong linear correlations. However, the microtexture indicators are not linearly correlated with the corresponding original texture indicators. D, WT (micro-texture power spectrum area) and ENT exhibit high degrees of numerical concentration for the same road sections and may be more statistically helpful in distinguishing the characteristics of the pavement performance decay of the road sections.
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Bachmann, F., Ralf Hielscher, and Helmut Schaeben. "Texture Analysis with MTEX – Free and Open Source Software Toolbox." Solid State Phenomena 160 (February 2010): 63–68. http://dx.doi.org/10.4028/www.scientific.net/ssp.160.63.

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The MATLAB™ toolbox MTEX provides a unique way to represent, analyse and interpret crystallographic preferred orientation, i.e. texture, based on integral (“pole figure”) or individual orientation (“EBSD”) measurements. In particular, MTEX comprises functions to import, analyse and visualize diffraction pole figure data as well as EBSD data, to estimate an orientation density function from either kind of data, to compute texture characteristics, to model orientation density functions in terms of model functions or Fourier coefficients, to simulate pole figure or EBSD data, to create publication ready plots, to write scripts for multiple use, and others. Thus MTEX is a versatile free and open-source software toolbox for texture analysis and modeling.
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Vadon, A., J. J. Heizmann, and C. Laruelle. "A Quantitative Texture Analysis of Pluri-Crystals by Texture Goniometry." Advances in X-ray Analysis 30 (1986): 429–37. http://dx.doi.org/10.1154/s0376030800021583.

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To understand how a material evolves - its crystal growth, topotaxy, twinning, phase transformation, plastic deformation, microstress, etc. - it is important to know the crystal orientations, either between them or in respect to the sample.The crystal texture of the material is quantified by the Orientation Distribution Function (O.D.F.). This function represents the part of the material volume having a given orientation. To compute this O.D.F, we must first measure one or several complete or incomplete pole figures and then analyse them either with Roe-Bunge's harmonic method or with Vadon, Ruer, Baro's vector method. In the case of a very sharp texture, the results obtained with the harmonic method are not good because developing a DIRAC function in spherical harmonics requires a high rank, hence a large number of pole figures. On the contrary, with the vector method, the results are good since discretizing amounts to developing on a step-function basis.
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Valentin, Romain, Karine Molvinger, Fran�oise Quignard, and Francesco Di Renzo. "Methods to Analyse the Texture of Alginate Aerogel Microspheres." Macromolecular Symposia 222, no. 1 (March 2005): 93–102. http://dx.doi.org/10.1002/masy.200550410.

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24

Huvenne, V. A. I., Ph Blondel, and J. P. Henriet. "Textural analyses of sidescan sonar imagery from two mound provinces in the Porcupine Seabight." Marine Geology 189, no. 3-4 (September 2002): 323–41. http://dx.doi.org/10.1016/s0025-3227(02)00420-6.

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Poussier, S., F. Maskali, B. Chalon, G. Vexiau, H. Boutley, E. Raffo, G. Karcher, and P. Y. Marie. "Analyse comparative de deux algorithmes de normalisation en imagerie TEP cérébrale chez le rat." Médecine Nucléaire 37, no. 5 (May 2013): 169. http://dx.doi.org/10.1016/j.mednuc.2013.03.131.

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26

Koralnik, M., B. Adamczyk-Cieślak, M. Kulczyk, and J. Mizera. "The effect of deformation degree on the microstructure of the 6060 aluminium alloy." Archives of Materials Science and Engineering 2, no. 85 (June 1, 2017): 80–85. http://dx.doi.org/10.5604/01.3001.0010.3429.

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Purpose: All results obtained in the present study allowed to analyse the changes in the microstructure and texture of the commercial 6060 aluminium alloy, after deformation process by severe plastic deformation. There were compare two deformation degree samples received by cumulative hydrostatic extrusion. Design/methodology/approach: The samples of the 6060 alloy were subjected to a onepass and three-passes extrusion process and next the age hardening. The microstructure changes were investigated by using transmission and scanning electron microscopy. To study the texture evolution the X-ray diffraction were made. Findings: The microscopic observations results presented the refinement of microstructure as a result of deformation process. The evolution of fibrous character of texture was observed. There were noted the disappearance of fibrous component <100> during subsequent deformation processes and generation the fibrous component <111> after high deformation degree. In addition, for each state, the presence of cubic texture component was recorded. Research limitations/implications: For the future research are planned to analyse changes in mechanical properties after hydrostatic extrusion combinate with age hardening of investigated materials. Originality/value: The paper focuses on the investigation of microstructure and texture evolution after modern method of plastic deformation.
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Popov, Antony T. "Multiscale Fractal Texture Analysis Using Morphological Techniques." Fractals 05, supp01 (April 1997): 125–31. http://dx.doi.org/10.1142/s0218348x97000693.

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Fractal dimension is used to analyse texture images. Since the fractal dimension remains unchanged under linear transformations, presented method is robust for dismissing effects caused by lighting and other extrinsic factors. The methods of mathematical morphology are used to calculate the fractal (Bouligand) dimension. A parallel implementation of morphological blanket covering is proposed.
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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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Benhamou, C. L., L. Pothuaud, and E. Lespessailles. "Caractérisation de la microarchitecture trabéculaire osseuse par analyse de texture." ITBM-RBM 21, no. 6 (December 2000): 351–58. http://dx.doi.org/10.1016/s1297-9562(00)90035-4.

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Lemaire, J. J., A. J. Frew, D. McArthur, A. A. Gorgulho, J. R. Alger, N. Salomon, C. Chen, E. J. Behnke, and A. A. F. DeSalle. "Exploration des connections de l’hypothalamus humain : analyse par tractographie et imagerie par tenseur de diffusion." Neurochirurgie 56, no. 6 (December 2010): 560. http://dx.doi.org/10.1016/j.neuchi.2010.10.113.

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Mendes-Martins, V., G. Coll, C. Botella, J. Coste, J. Gabrillargue, and J. J. Lemaire. "Analyse morphométrique du noyau sous-thalamique en imagerie par résonance magnétique nucléaire à 1.5 Tesla." Neurochirurgie 57, no. 4-6 (September 2011): 276. http://dx.doi.org/10.1016/j.neuchi.2011.09.083.

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Fu, Yuanyuan, Guijun Yang, Zhenhai Li, Xiaoyu Song, Zhenhong Li, Xingang Xu, Pei Wang, and Chunjiang Zhao. "Winter Wheat Nitrogen Status Estimation Using UAV-Based RGB Imagery and Gaussian Processes Regression." Remote Sensing 12, no. 22 (November 18, 2020): 3778. http://dx.doi.org/10.3390/rs12223778.

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Predicting the crop nitrogen (N) nutrition status is critical for optimizing nitrogen fertilizer application. The present study examined the ability of multiple image features derived from unmanned aerial vehicle (UAV) RGB images for winter wheat N status estimation across multiple critical growth stages. The image features consisted of RGB-based vegetation indices (VIs), color parameters, and textures, which represented image features of different aspects and different types. To determine which N status indicators could be well-estimated, we considered two mass-based N status indicators (i.e., the leaf N concentration (LNC) and plant N concentration (PNC)) and two area-based N status indicators (i.e., the leaf N density (LND) and plant N density (PND)). Sixteen RGB-based VIs associated with crop growth were selected. Five color space models, including RGB, HSV, L*a*b*, L*c*h*, and L*u*v*, were used to quantify the winter wheat canopy color. The combination of Gaussian processes regression (GPR) and Gabor-based textures with four orientations and five scales was proposed to estimate the winter wheat N status. The gray level co-occurrence matrix (GLCM)-based textures with four orientations were extracted for comparison. The heterogeneity in the textures of different orientations was evaluated using the measures of mean and coefficient of variation (CV). The variable importance in projection (VIP) derived from partial least square regression (PLSR) and a band analysis tool based on Gaussian processes regression (GPR-BAT) were used to identify the best performing image features for the N status estimation. The results indicated that (1) the combination of RGB-based VIs or color parameters only could produce reliable estimates of PND and the GPR model based on the combination of color parameters yielded a higher accuracy for the estimation of PND (R2val = 0.571, RMSEval = 2.846 g/m2, and RPDval = 1.532), compared to that based on the combination of RGB-based VIs; (2) there was no significant heterogeneity in the textures of different orientations and the textures of 45 degrees were recommended in the winter wheat N status estimation; (3) compared with the RGB-based VIs and color parameters, the GPR model based on the Gabor-based textures produced a higher accuracy for the estimation of PND (R2val = 0.675, RMSEval = 2.493 g/m2, and RPDval = 1.748) and the PLSR model based on the GLCM-based textures produced a higher accuracy for the estimation of PNC (R2val = 0.612, RMSEval = 0.380%, and RPDval = 1.601); and (4) the combined use of RGB-based VIs, color parameters, and textures produced comparable estimation results to using textures alone. Both VIP-PLSR and GPR-BAT analyses confirmed that image textures contributed most to the estimation of winter wheat N status. The experimental results reveal the potential of image textures derived from high-definition UAV-based RGB images for the estimation of the winter wheat N status. They also suggest that a conventional low-cost digital camera mounted on a UAV could be well-suited for winter wheat N status monitoring in a fast and non-destructive way.
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Haffen, E. "Le ralentissement psychomoteur : une dimension à (re)découvrir ?" European Psychiatry 29, S3 (November 2014): 578–79. http://dx.doi.org/10.1016/j.eurpsy.2014.09.277.

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Le ralentissement psychomoteur (RPM) est une dimension clinique présente dans de nombreuses maladies mentales. S’il est l’un des symptômes cardinaux de la dépression unipolaire, on le retrouve également dans le trouble bipolaire et la schizophrénie mais sans qu’il y ait une véritable différence sémiologique selon la pathologie concernée.Le RPM se caractérise non seulement par une composante motrice mais également psychique et langagière, qui inclut des processus perceptifs et cognitifs impliqués dans le contrôle, la planification, la programmation et l’exécution du mouvement.Les outils d’évaluation disponibles (imagerie cérébrale, analyse génétique, analyse rythmique, analyse par tracker vidéo, explorations neuropsychologiques) permettent aujourd’hui de mieux caractériser l’ensemble de ses dimensions. L’hypothèse d’un dysfonctionnement dopaminergique est étayée par de nombreux travaux avec des atteintes fonctionnelles au niveau des circuits sous-corticaux et pré-frontaux.Le RPM s’accompagne d’une altération fonctionnelle majeure et requiert ainsi une attention particulière en termes d’ajustement thérapeutique d’autant que se pose à l’heure actuelle la question de son impact pronostique (persistance en dehors des épisodes aigus, réponse aux traitements, rechute et récurrence).
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Meyer, Colette. "CARTOGRAPHIE DU CHÂTAIGNIER EN ALSACE PAR IMAGERIE SATELLITE MULTI-DATE." Revue Française de Photogrammétrie et de Télédétection 1, no. 211-212 (December 6, 2015): 25–31. http://dx.doi.org/10.52638/rfpt.2015.538.

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Parmi toutes les essences qui peuplent la forêt alsacienne, le châtaignier est considéré comme un arbre d’avenir face aux enjeux du réchauffement climatique. Cette essence a fait l’objet d’une étude particulière dans le cadre d’un projet franco-allemand intégré au programme européen Interreg IV A Rhin supérieur. D’une durée de trois ans, cette étude avait pour objectif de développer des stratégies de préservation et de valorisation de ces châtaigneraies. Elle a ainsiporté sur la conservation des paysages forestiers, sur la valorisation du bois et des fruits, ainsi que sur la préservation des châtaigneraies face au chancre qui menace les peuplements.Dans le cadre de ce programme, le SERTIT a développé une méthode pour produire une cartographie détaillée et à jour des zones de châtaigniers sur toute l’Alsace. La méthodologie pour distinguer les châtaigniers des autres essences forestières a été développée à partir d’un choix ciblé d’images satellites acquises à différentes saisons et des données de terrain de placettes géo localisant des châtaigneraies. Ainsi des images SPOT5 et ALOS AVNIR-2 multi-temporelles couvrant différentes phases du cycle de développement annuel du châtaignier (au printemps et en été) ont été utilisées.L’étude est basée sur une analyse des caractéristiques spectrales pour les principaux feuillus à partir d’échantillons de terrain pour les différentes images. Ainsi, l’analyse des signatures spectrales a permis d’identifier les images permettant une différenciation des châtaigniers, ce sont celles acquises au début du printemps et en été. Elles correspondent aux caractéristiques particulières propres à cette essence qui sont son développement foliaire tardif par rapport aux autres feuillus et sa floraison abondante. Les résultats de cette cartographie générée sur l’ensemble de la région Alsace ont été validés lors de campagnes de terrain, cette validation qui n’a été que partielle a pourtant montré une bonne précision de détection des peuplements de châtaigniers matures qui est de 85%.
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Sichi, Olga Gómez, Philippe Blondel, Eulàlia Gràcia, and Juan José Dañobeitia. "Quantitative textural analyses of TOBI sonar imagery along the Almería Canyon, Almería Margin, Alborán Sea, SE Spain." Geological Society, London, Special Publications 244, no. 1 (2005): 141–54. http://dx.doi.org/10.1144/gsl.sp.2005.244.01.09.

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36

Kurtz, Camille, Pierre Gançarski, Anne Puissant, and Nicolas Passat. "Approches Multi-Hiérarchiques pour l'Analyse d'Images de Télédétection." Revue Française de Photogrammétrie et de Télédétection, no. 205 (February 21, 2014): 19–35. http://dx.doi.org/10.52638/rfpt.2014.10.

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Au cours de la dernière décennie, la télédétection par imagerie satellitaire a connu plusieurs révolutions, liées d'une part à l'augmentation spectaculaire du nombre de dispositifs d'acquisition, et d'autre part aux progrès des capteurs tant en termes de résolutions spatiale et temporelle que spectrale. Dans ce contexte, de nouvelles problématiques sont apparues,notamment en traitement et analyse d'images. L'un des axes de recherche les plus prometteurs pour traiter ces problématiques s'appuie sur la notion de hiérarchie, qui peut se décliner sous plusieurs formes et ainsi permettre de traiter plusieurs types de tâches, du traitement de bas-niveau jusqu'à l'analyse de haut niveau. Dans cet article, nous décrivons certaines tendances récentes liées à ces approches hiérarchiques.
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Ameli, Roxana, Simon Mure, Charles R. G. Guttmann, Thomas Grenier, Hugues Benoit-Cattin, and François Cotton. "Analyse dynamique hebdomadaire du développement péri-veinulaire des lésions actives de SEP par imagerie de susceptibilité magnétique." Journal of Neuroradiology 43, no. 2 (March 2016): 91–93. http://dx.doi.org/10.1016/j.neurad.2016.01.056.

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38

Engler, O. "Comparison of X-ray and electron backscatter diffraction textures for back-annealed Al–Mg alloys." Journal of Applied Crystallography 42, no. 6 (November 7, 2009): 1147–57. http://dx.doi.org/10.1107/s0021889809041685.

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The potential of electron backscatter diffraction (EBSD) to determine integral macrotexture data is explored by comparing EBSD-derived textures with standard X-ray texture results. The comparison is performed for an Al–Mg alloy AA 5005 in the cold-rolled and various back-annealed states in order to analyse the impact of the microstructural state on the quality of EBSD-based macrotextures. The number of EBSD single orientation measurements necessary to represent a texture adequately is determined by way of exploring the convergence of the statistical parameter ρ, which represents the relative mean square deviation between the EBSD and X-ray-based textures. The effect of EBSD filtering tools and the impact of sampling step size on the statistical significance of EBSD data are investigated. Several means to reduce the number of data points without compromising the accuracy of the texture results as an input for subsequent texture simulation are addressed.
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Faridah, Anni, Riski Gusri Utami, Ruhul Fitri Rosel, and Mohd Salehuddin Mohd Zhari. "Whole Tilapia Fish Balls: Texture, Calcium, and Phosphorus." IOP Conference Series: Earth and Environmental Science 1228, no. 1 (August 1, 2023): 012011. http://dx.doi.org/10.1088/1755-1315/1228/1/012011.

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Abstract Indonesian love beef meatballs. However, beef meatballs have a high saturated fat content and are expensive. Tilapia fish can replace meatballs’ primary protein source. However, tilapia has a low fillet yield of 20-30%, producing 65-89% waste. The use of whole tilapia in the production of fish balls can increase the benefits of calcium- and phosphorus-rich fish by-products. Osteoporosis-prone individuals need calcium and phosphorus-rich foods. Notwithstanding, our preliminary research showed whole tilapia fish balls have a low texture; thus, adding a gelling agent (carrageenan) is necessary. Carrageenan has not been examined in whole tilapia fish balls. This study aimed to analyse whole tilapia fish balls’ sensory and nutritional qualities with 1%, 2%, 3%, 4%, and 5% carrageenan. The study used Complete Randomized Designs (CRD) with three repetitions. ANOVA and Duncan’s test were used to analyse sensory data. The results showed that more carrageenan improved the texture of the whole fish balls. Therefore, it is recommended to use 5% carrageenan to make whole tilapia fish balls chewy and dense. The ash, fat, protein, calcium, and phosphorus content of whole tilapia fish balls were higher than that of tilapia fillet fish balls, but the water content and carbohydrates were lower. Adding 5% carrageenan enhanced the water content, ash, protein, calcium, and phosphorus, reducing the carbohydrate for both whole and fillet tilapia balls. Whole tilapia fish balls had ± 9 times more calcium than fillet balls (417.23 mg/100 gr) and ± 32 times more phosphorus (231.22 mg/100 gr). The calcium and phosphorus content of whole tilapia fish balls is roughly equal to the daily recommended value of 2:1. This study suggests that by eating 250-350 grams daily, people prone to osteoporosis can meet their calcium and phosphorus levels needs.
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Muktiningrum, Tyas Arie, Gusti Fauza, Setyaningrum Ariviani, Dimas R. A. Muhammad, and Dian Rachmawanti Affandi. "Sensory profile analysis of chocolate drinks using quantitative descriptive analysis (QDA)." E3S Web of Conferences 344 (2022): 04005. http://dx.doi.org/10.1051/e3sconf/202234404005.

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This study aims to analyse the sensory profile of a low-fat chocolate drink. The chocolate drink is being developed in laboratory of food science and technology department at Universitas Sebelas Maret. The QDA was applied to characterize the sensory profile of the developed product (sample D) and four commercial products (sample A, B, C, and E). 13 panellists were trained to evaluate those samples based on appearance, odour, flavour, basic taste and texture. Further, ANOVA was utilized to differentiate the samples, while PCA and Spider web were applied to analyse the sensory profile of the samples. The results showed that sample D was quite similar to sample A (dominated by cocoa aroma, cocoa flavour, sandiness, undissolved particles, colour, white-cream layer, thickness texture and bitter taste), whereas sample C had similar characteristic to sample E (represented by milky aroma, milky flavour, vanilla flavour and creamy texture). Meanwhile, sample B differed from others for representing malt odour and malt flavour attributes. It is implied from the result that sample A would be the potential competitor for the developed product since they may be in the same market segmentation. Therefore, the strategy of improving the developed product should take a look at the sensory attributes of sample A as a benchmarking.
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Ceneno, Jorge Antonio Silva, Regina Tiemy Kishi, and Edson Aparecido Mitishita. "Detection of areas for rainwater harvesting using airborne laser scanner and aerial imagery." Revue Française de Photogrammétrie et de Télédétection, no. 198-199 (April 21, 2014): 25–29. http://dx.doi.org/10.52638/rfpt.2012.68.

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Cet article présente une méthode d’identification des toits pour la récupération des eaux pluviales, basée sur l’utilisation des données d’un laser à balayage et d’imagerie visible et proche infrarouge. La discrimination automatique des surfaces couvertes de végétation et de toits s’avère difficile lorsque seule la hauteur des pixels est utilisée ; la procédure s’améliore lorsque la variation locale de l’altitude, c’est-à-dire la texture, est analysée. L’image obtenue par balayage laser est d’abord seuillée en fonction de la hauteur. La morphologie mathématique est également utilisée pour sélectionner les plus grandes surfaces, plus propices à la récupération des eaux pluviales. Lorsque la densité du nuage de points est trop faible, l’analyse conjointe des données laser et des photographies aériennes permet une meilleurediscrimination de la végétation et des toits. L'étude démontre la viabilité d’une utilisation conjointe du laser à balayage et de la photographie aérienne pour une telle application et la puissance de l’analyse texturale pour la discrimination.
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42

Foucart, Jean-Michel, Rufino Felizardo, Christophe Pizelle, and Jérôme Bourriau. "Indications des examens radiologiques en orthopédie dento-faciale." L'Orthodontie Française 83, no. 1 (March 2012): 59–72. http://dx.doi.org/10.1051/orthodfr/2012001.

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La réduction des risques liés à l’utilisation des rayons ionisants est une préoccupation constante des praticiens mais aussi des législateurs qui ont transposé cette règle éthique dans le Code de la Santé Publique. Cette réduction des risques s’exprime à travers l’un des principes fondamentaux en radioprotection : la justification de tous les actes de radiodiagnostic. En application directe de ce principe, l’État français a publié, en 2006, un guide des indications des examens radiologiques en odontostomatologie. Néanmoins, celui-ci n’abordait que très partiellement le domaine de l’orthodontie, domaine dont les techniques radiologiques en pleine évolution rendent nécessaire une actualisation permanente des recommandations.L’objectif de cet article est donc, à partir d’une analyse systématisée et critique de la littérature, de proposer des recommandations actualisées en imagerie orthodontique.
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43

Laba, Magdeline, Stephen Smith, Patrick Sullivan, William Philpot, and Philippe Baveye. "Influence of wavelet type on the classification of marsh vegetation from satellite imagery using a combination of wavelet texture and statistical component analyses." Canadian Journal of Remote Sensing 33, no. 4 (January 2007): 260–65. http://dx.doi.org/10.5589/m07-034.

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44

Lacoste, Marion, Claude Alain Maurage, Benoit Derré, Henri Arthur Leroy, Marc Baroncini, Nicolas Reyns, Jean Pierre Pruvo, and Christine Delmaire. "Faisabilité de la corrélation anatomo-radiologique entre imagerie en tenseur de diffusion et analyse histologique des tumeurs glialess." Journal of Neuroradiology 46, no. 2 (March 2019): 90–91. http://dx.doi.org/10.1016/j.neurad.2019.01.014.

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45

SALMENKALLIO-MARTTILA, M., K. ROININEN, and K. AUTIO. "Effects of gluten and transglutaminase on microstructure, sensory characteristics and instrumental texture of oat bread." Agricultural and Food Science 13, no. 1-2 (December 4, 2008): 138. http://dx.doi.org/10.2137/1239099041838003.

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Effects of added gluten and transglutaminase on microstructure, instrumental texture and sensory characteristics of bread baked with 51% wholemeal oat flour were compared in order to determine how changes in the state of macromolecules – protein and starch – correlate with changes in sensory and instrumental structure. Light microscopy, instrumental texture profile analysis, and descriptive sensory analysis were used to analyse the test breads. Addition of gluten and transglutaminase affected the structure of the protein network and distribution of water between the protein and starch phases. The differences in microstructure were quantified by determining the areas of starch and protein in the micrographs by image analysis. Breads baked with added gluten and water were softer and less gummy than the oat and wheat reference breads in the texture profile analysis. Addition of transglutaminase made the breads harder and gummier than the breads baked without the added enzyme. In the descriptive sensory analysis breads baked with added gluten or added gluten and water were evaluated as more soft and springy than the reference oat bread. Sensory characteristics of bread texture correlated well with the texture and microstructure measured instrumentally.;
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46

Song, Kuk Hyun, Han Sol Kim, and Won Yong Kim. "Microstructure and Texture Development in Pure Ta Sheets Processed by Conventional Rolling and Cross Roll Rolling." Materials Science Forum 706-709 (January 2012): 2652–56. http://dx.doi.org/10.4028/www.scientific.net/msf.706-709.2652.

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To evaluate the effect of rolling process on microstructures and textures development, this work was carried out using pure Ta sheets. For this work, conventional rolling (CR) and cross roll rolling (CRR) as a deformation process were introduced, pure Ta sheets were cold rolled to 90% in thickness reduction. After this, to obtain the recrystallized microstructure on cold rolled materials, the recrystallization heat-treatment was performed at 1200°C for 60 min under the high vacuum state. Also, to analyse the grain boundary character distributions of the annealed sheets, electron back-scattered diffraction method was introduced. As an experimental result, increase in strain rate led to the development of texture with its texture component of <111> at conventional rolling and cross roll rolling, in common. Therefore, in this study, we systematically discussed the texture development due to increase in effective strain.
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47

Webster, P. J. "Analyse des contraintes résiduelles et de la texture dans les matériaux : applications industrielles." Journal de Physique IV (Proceedings) 103 (February 2003): 305–19. http://dx.doi.org/10.1051/jp4:200300012.

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48

Loosvelt, L., H. Vernieuwe, V. R. N. Pauwels, B. De Baets, and N. E. C. Verhoest. "Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling." Hydrology and Earth System Sciences 17, no. 2 (February 1, 2013): 461–78. http://dx.doi.org/10.5194/hess-17-461-2013.

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Abstract. Compositional data, such as soil texture, are hard to deal with in the geosciences as standard statistical methods are often inappropriate to analyse this type of data. Especially in sensitivity analysis, the closed character of the data is often ignored. To that end, we developed a method to assess the local sensitivity of a model output with resect to a compositional model input. We adapted the finite difference technique such that the different parts of the input are perturbed simultaneously while the closed character of the data is preserved. This method was applied to a hydrologic model and the sensitivity of the simulated soil moisture content to local changes in soil texture was assessed. Based on a high number of model runs, in which the soil texture was varied across the entire texture triangle, we identified zones of high sensitivity in the texture triangle. In such zones, the model output uncertainty induced by the discrepancy between the scale of measurement and the scale of model application, is advised to be reduced through additional data collection. Furthermore, the sensitivity analysis provided more insight into the hydrologic model behaviour as it revealed how the model sensitivity is related to the shape of the soil moistureretention curve.
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Liu, Huaipeng, Xiaoyan Su, Chuancai Zhang, and Huijun An. "Landscape tree species recognition using RedEdge-MX: Suitability analysis of two different texture extraction forms under MLC and RF supervision." Open Geosciences 14, no. 1 (January 1, 2022): 985–94. http://dx.doi.org/10.1515/geo-2022-0416.

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Abstract The size of the texture extraction window impacts image tree species classification, and the determination of the optimal texture extraction window requires the supervision of a specific classifier for accuracy. Therefore, it is necessary to analyse which kind of classifier is more suitable and should be to choose. In this study, we extracted eight types of textures, namely mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation, changed the window size by gradient increase and used maximum likelihood classification (MLC) and random forest (RF) to supervise and determine their optimal extraction windows, respectively. Finally, the optimised time consumption and classification accuracy for tree species classification was identified. The time consumption of MLC was significantly less than that of RF; however, neither was very long; for most textures, the optimal texture extraction window determined by MLC supervision was larger than that determined by RF supervision; in the classification of most feature sets, the overall accuracy obtained by MLC was less than that of RF. Because the time consumption of the texture extraction was much greater than that of the image classification, the comprehensive trade-off indicates that using RF supervision to determine the optimal window for texture extraction was more conducive to tree species recognition.
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Loosvelt, L., H. Vernieuwe, V. R. N. Pauwels, B. De Baets, and N. E. C. Verhoest. "Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling." Hydrology and Earth System Sciences Discussions 9, no. 7 (July 25, 2012): 8841–83. http://dx.doi.org/10.5194/hessd-9-8841-2012.

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Abstract. Compositional data, such as soil texture, are hard to deal with in the geosciences as standard statistical methods are often inappropriate to analyse this type of data. Especially in sensitivity analysis, the closed character of the data is often ignored. To that end, we developed a method to assess the local sensitivity of a model output w.r.t. a compositional model input. We adapted the finite difference technique such that the different parts of the input are perturbed simultaneously while the closed character of the data is preserved. We applied this method to a hydrologic model and assessed the sensitivity of the simulated soil moisture content to local changes in soil texture. Based on a high number of model runs, in which the soil texture was varied across the entire texture triangle, we identified zones of high sensitivity in the texture triangle. In such zones, the model output uncertainty induced by the discrepancy between the scale of measurement and the scale of model application, is advised to be reduced through additional data collection. Furthermore, the sensitivity analysis provided more insight into the hydrologic model behaviour as it revealed how the model sensitivity is related to the shape of the soil moisture retention curve.
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