Centre de documentation
scientifique

Improving deep learning on point cloud by maximizing mutual information across layers / Di Wang in Pattern recognition, vol 131 (November 2022)  

Public [article]  inPattern recognition > vol 131 (November 2022) . - n° 108892 Titre : Improving deep learning on point cloud by maximizing mutual information across layers Type de document : Article/Communication Auteurs : Di Wang, Auteur ; Lulu Tang, Auteur ; Xu Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] entropie de Shannon [Termes IGN] information sémantique [Termes IGN] segmentation sémantique [Termes IGN] semis de points [Termes IGN] transformation géométrique [Termes IGN] vision par ordinateur [Termes IGN] visualisation 3D Résumé : (auteur) It is a fundamental and vital task to enhance the perception capability of the point cloud learning network in 3D machine vision applications. Most existing methods utilize feature fusion and geometric transformation to improve point cloud learning without paying enough attention to mining further intrinsic information across multiple network layers. Motivated to improve consistency between hierarchical features and strengthen the perception capability of the point cloud network, we propose exploring whether maximizing the mutual information (MI) across shallow and deep layers is beneficial to improve representation learning on point clouds. A novel design of Maximizing Mutual Information (MMI) Module is proposed, which assists the training process of the main network to capture discriminative features of the input point clouds. Specifically, the MMI-based loss function is employed to constrain the differences of semantic information in two hierarchical features extracted from the shallow and deep layers of the network. Extensive experiments show that our method is generally applicable to point cloud tasks, including classification, shape retrieval, indoor scene segmentation, 3D object detection, and completion, and illustrate the efficacy of our proposed method and its advantages over existing ones. Our source code is available at https://github.com/wendydidi/MMI.git. Numéro de notice : A2022-780 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : https://doi.org/10.1016/j.patcog.2022.108892 Date de publication en ligne : 08/07/2022 En ligne : https://doi.org/10.1016/j.patcog.2022.108892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101859 [article]

Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran / Sahand Seraj in Geo-spatial Information Science, vol 25 n° 3 (October 2022)  

Public [article]  inGeo-spatial Information Science > vol 25 n° 3 (October 2022) . - pp 399 - 41 Titre : Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran Type de document : Article/Communication Auteurs : Sahand Seraj, Auteur ; Mahmoud Reza Delavar, Auteur Année de publication : 2022 Article en page(s) : pp 399 - 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] cartographie géologique [Termes IGN] classification floue [Termes IGN] entropie de Shannon [Termes IGN] forage [Termes IGN] granulométrie (pétrologie) [Termes IGN] hydrocarbure [Termes IGN] incertitude géométrique [Termes IGN] Iran [Termes IGN] prospection minérale [Termes IGN] sous ensemble flou [Termes IGN] système d'information géographique Résumé : (auteur) It is well agreed that geologic risk occurs during hydrocarbon exploration because diverse uncertainties accompany the entire hydrocarbon system parameters such as the source rock, reservoir rock, trap and seal rock. In order to overcome such attributes with uncertainties, a number of soft computing methods are used. Information granules could be provided by the Rough Fuzzy Set Granulation (RFSG) with a thorough quality evaluation. This is capable of attribute reduction that has been claimed to be essential in investigating the hydrocarbon systems. This paper is an endeavor to recommend a Geospatial Information System (GIS)-based model with the aim of categorizing the hydrocarbon structures map consistent with the uncertainty range concepts of geologic risk in the rough fuzzy sets and granular computing. The model used the RFSG for the attribute reduction by a Decision Logic language (DL-language). The RFSG was employed in order to classify hydrocarbon structures according to geological risk and extract the fuzzy rules with a predefined range of uncertainty. In order to assess the precisions of the fuzzy decisions on the hydrocarbon structure classification, the fuzzy entropy and fuzzy cross-entropy are applied. The proposed RFSG model applied for 62 structures as the training data, average fuzzy entropy has been calculated as 0.85, whereas the average fuzzy cross-entropy has been calculated 0.18. As it can be discerned, just seven structures had cross-entropies greater than 0.1, while three structures were larger than 0.3. It is implied that the precision of the proposed model is about 89%. The results yielded two reductions for the condition attributes and 11 fuzzy rules being filtered by the granular computing values. Numéro de notice : A2022-724 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2021.2020600 Date de publication en ligne : 03/02/2022 En ligne : https://doi.org/10.1080/10095020.2021.2020600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101667 [article]

Remote sensing and phytoecological methods for mapping and assessing potential ecosystem services of the Ouled Hannèche Forest in the Hodna Mountains, Algeria / Amal Louail in Forests, Vol 13 n° 8 (August 2022)  

Public [article]  inForests > Vol 13 n° 8 (August 2022) . - n° 1159 Titre : Remote sensing and phytoecological methods for mapping and assessing potential ecosystem services of the Ouled Hannèche Forest in the Hodna Mountains, Algeria Type de document : Article/Communication Auteurs : Amal Louail, Auteur ; François Messner, Auteur ; Yamna Djellouli, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Algérie [Termes IGN] analyse multicritère [Termes IGN] carte thématique [Termes IGN] entropie de Shannon [Termes IGN] forêt méditerranéenne [Termes IGN] image Landsat-8 [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] protection de la biodiversité [Termes IGN] relevé phytoécologique [Termes IGN] service écosystémique Résumé : (auteur) Regardless of their biogeographic origins or degree of artificialization, the world’s forests are a source of a wide range of ecosystem services (ES). However, the quality and quantity of these services depend on the type of forest studied and its phytogeographic context. Our objective is to transpose the concept of ES, in particular, the assessment of forest ES, to the specific Mediterranean context of the North African mountains, where this issue is still in its infancy and where access to the data needed for assessment remains difficult. Our work presents an introductory approach, allowing us to set up methodological and scientific milestones based on open-access remote sensing data and already tested geospatial processing associated with phytoecological surveys to assess the ES provided by forests in an Algerian study area. Specifically, several indicators used to assess (both qualitatively and quantitatively) the potential ES of the Ouled Hannèche forest, a forest located in the Hodna Mountains, are derived from LANDSAT 8 OLI images from 2017 and an ALOS AW3D30 DSM. The qualitative ES typology is jointly based on an SVM classification of topographically corrected LANDSAT images and a geomorphic-type classification using the geomorphon method. NDVI is a quantitative estimator of many plant ecosystem functions related to ES. It highlights the variations in the provision of ES according to the types of vegetation formations present. It serves as a support for estimating spectral heterogeneity through Rao’s quadratic entropy, which is considered a relative indicator of biodiversity at the landscape scale. The two previous variables (the multitemporal NDVI and Rao’s Q), completed by the Shannon entropy method applied to the geomorphon classes as a proxy for topo-morphological heterogeneity, constitute the input variables of a quantitative map of the potential supply of ES in the forest determined by Spatial Multicriteria Analysis (SMCA). Ultimately, our results serve as a useful basis for land-use planning and biodiversity conservation. Numéro de notice : A2022-654 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13081159 Date de publication en ligne : 22/07/2022 En ligne : https://doi.org/10.3390/f13081159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101502 [article]

A constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data / Jing Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 114 - 136 Titre : A constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data Type de document : Article/Communication Auteurs : Jing Yang, Auteur ; Jingwen Dong, Auteur ; Yizhong Sun, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 114 - 136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] délimitation de frontière [Termes IGN] données multisources [Termes IGN] entropie de Shannon [Termes IGN] espace rural [Termes IGN] estimation par noyau [Termes IGN] Kiangsou (Chine) [Termes IGN] programmation par contraintes [Termes IGN] transformation en ondelettes [Termes IGN] urbanisation [Termes IGN] zonage (urbanisme) [Termes IGN] zone rurale [Termes IGN] zone urbaine Résumé : (auteur) Studies on urban–rural fringes, which represent regions facing various urbanization problems caused by rapid expansion, have steadily increased in recent years. However, problems persist in the quantitative delimitation of such regions. Based on the characteristics of abrupt urbanization-level changes in urban–rural fringe areas, we propose a constraint-based method in this study to detect the urban–rural fringes of cities with a spatial polycentric structure of ‘Main center–Subcenter’ based on data from multiple sources. We used the proposed approach to delimitate the fringe areas of Jiangyin and Zhangjiagang and identify their urban main center and subcenter pre-defined by their city master plans, towns, and rural hinterlands. Comparison of the identified results of different single urbanization indices, a single detection center, kernel density estimation, and a single constraint revealed that the patch density and Shannon’s diversity index of the proposed method were higher in urban–rural fringes and smaller in city centers and rural hinterlands. This suggests that the landscape of urban–rural fringes delimitated by the proposed method is more fragmented, diverse, and complicated, thereby performing better. This study is significant for future urban spatial analysis, planning, and management. Numéro de notice : A2022-045 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1080/13658816.2021.1876236 Date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.1080/13658816.2021.1876236 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99404 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2022011	SL	Revue	Centre de documentation	Revues en salle	Disponible

A multi-scale representation model of polyline based on head/tail breaks / Pengcheng Liu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 11 (November 2020) . - pp 2275 - 2295 Titre : A multi-scale representation model of polyline based on head/tail breaks Type de document : Article/Communication Auteurs : Pengcheng Liu, Auteur ; Tianyuan Xiao, Auteur ; Jia Xiao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2275 - 2295 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de Douglas-Peucker [Termes IGN] analyse de groupement [Termes IGN] entropie de Shannon [Termes IGN] généralisation cartographique automatisée [Termes IGN] polyligne [Termes IGN] représentation multiple [Termes IGN] série de Fourier [Vedettes matières IGN] Généralisation Résumé : (auteur) This paper proposes a model to quantify the multiscale representation of a polyline based on iterative head/tail breaks. A polyline is first transformed into a corresponding Fourier descriptor consisting of normalized Fourier-series-expansion coefficients. Then, the most significant finite components of the Fourier descriptor are selected and ranked to constitute the polyline constrained Fourier descriptor. Using Shannon’s information theory, information content of the constrained Fourier-descriptor components is defined. Next, head/tail breaks are introduced to iteratively divide the constrained Fourier descriptor into head and tail components according to the heavy-tailed distribution of information contents. Thus, simplified polylines are reconstructed using ordered heads generated from head/tail breaks. Finally, the radical law is introduced and applied to model multiscale polyline representation by quantifying the scale of each simplified polyline. Three experiments are designed and conducted to evaluate the proposed model. The results demonstrate that the proposed model is valid and efficient for quantifying multiscale polyline representation. Numéro de notice : A2020-615 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1753203 Date de publication en ligne : 22/04/2020 En ligne : https://doi.org/10.1080/13658816.2020.1753203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95988 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2020111	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Effect of forest structure on stand productivity in Central European forests depends on developmental stage and tree species diversity / Laura Zeller in Forest ecology and management, vol 434 (28 February 2019)  

Permalink

Retina-inspired image and video coding / Effrosyni Doutsi (2017)  

Permalink

Geo-temporal Twitter demographics / Paul A. Longley in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)  

Permalink