Centre de documentation
scientifique

Semantic feature-constrained multitask siamese network for building change detection in high-spatial-resolution remote sensing imagery / Qian Shen in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 189 (July 2022) . - pp 78 - 94 Titre : Semantic feature-constrained multitask siamese network for building change detection in high-spatial-resolution remote sensing imagery Type de document : Article/Communication Auteurs : Qian Shen, Auteur ; Jiru Huang, Auteur ; Min Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 78 - 94 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection de changement [Termes IGN] détection du bâti [Termes IGN] données qualitatives [Termes IGN] estimation quantitative [Termes IGN] fusion d'images [Termes IGN] image à haute résolution [Termes IGN] image multibande [Termes IGN] jeu de données [Termes IGN] réseau neuronal siamois Résumé : (auteur) In the field of remote sensing applications, semantic change detection (SCD) simultaneously identifies changed areas and their change types by jointly conducting bitemporal image classification and change detection. It facilitates change reasoning and provides more application value than binary change detection (BCD), which offers only a binary map of the changed/unchanged areas. In this study, we propose a multitask Siamese network, named the semantic feature-constrained change detection (SFCCD) network, for building change detection in bitemporal high-spatial-resolution (HSR) images. SFCCD conducts feature extraction, semantic segmentation and change detection simultaneously, where change detection and semantic segmentation are the main and auxiliary tasks, respectively. For the segmentation task, ResNet50 is used to conduct image feature extraction, and the extracted semantic features are provided to execute the change detection task via a series of jump connections. For the change detection task, a global channel attention (GCA) module and a multiscale feature fusion (MSFF) module are designed, where high-level features offer training guidance to the low-level feature maps, and multiscale features are fused with multiple convolutions that possess different receptive fields. In bitemporal HSR images with different view angles, high-rise buildings have different directional height displacements, which generally cause serious false alarms for common change detection methods. However, known public building change detection datasets often lack buildings with height displacement. We thus create the Nanjing Dataset (NJDS) and design the aforementioned network structures and modules to target this issue. Experiments for method validation and comparison are conducted on the NJDS and two additional public datasets, i.e., the WHU Building Dataset (WBDS) and Google Dataset (GDS). Ablation experiments on the NJDS show that the joint utilization of the GCA and MSFF modules performs better than several classic modules, including atrous spatial pyramid pooling (ASPP), efficient spatial pyramid (ESP), channel attention block (CAB) and global attention upsampling (GAU) modules, in dealing with building height displacement. Furthermore, SFCCD achieves higher accuracy in terms of the OA, recall, F1-score and mIoU measures than several state-of-the-art change detection methods, including deeply supervised image fusion network (DSIFN), the dual-task constrained deep Siamese convolutional network (DTCDSCN), and multitask U-Net (MTU-Net). Numéro de notice : A2022-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.05.001 Date de publication en ligne : 12/05/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.05.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100762 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2022071	SL	Revue	Centre de documentation	Revues en salle	Disponible

Line-based deep learning method for tree branch detection from digital images / Rodrigo L. S. Silva in International journal of applied Earth observation and geoinformation, vol 110 (June 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 110 (June 2022) . - n° 102759 Titre : Line-based deep learning method for tree branch detection from digital images Type de document : Article/Communication Auteurs : Rodrigo L. S. Silva, Auteur ; José Marcato Junior, Auteur ; Laisa Almeida, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102759 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] branche (arbre) [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] données qualitatives [Termes IGN] estimation quantitative [Termes IGN] image à haute résolution [Termes IGN] ligne (géométrie) [Termes IGN] transformation de Hough Résumé : (auteur) Preventive maintenance of power lines, including cutting and pruning of tree branches, is essential to avoid interruptions in the energy supply. Automatic methods can support this risky task and also reduce time-consuming. Here, we propose a method in which the orientation and the grasping positions of tree branches are estimated. The proposed method firstly predicts the straight line (representing the tree branch extension) based on a convolutional neural network (CNN). Secondly, a Hough transform is applied to estimate the direction and position of the line. Finally, we estimate the grip point as the pixel point with the highest probability of belonging to the line. We generated a dataset based on internet searches and annotated 1868 images considering challenging scenarios with different tree branch shapes, capture devices, and environmental conditions. Ten-fold cross-validation was adopted, considering 90% for training and 10% for testing. We also assessed the method under corruptions (gaussian and shot) with different severity levels. The experimental analysis showed the effectiveness of the proposed method reporting F1-score of 96.78%. Our method outperformed state-of-the-art Deep Hough Transform (DHT) and Fully Convolutional Line Parsing (F-Clip). Numéro de notice : A2022-550 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102759 Date de publication en ligne : 09/05/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101153 [article]

Excel data analysis / Hector Guerrero (2019)  

Public Titre : Excel data analysis : modeling and simulation Type de document : Guide/Manuel Auteurs : Hector Guerrero, Auteur Mention d'édition : 2ème édition Editeur : Springer Nature Année de publication : 2019 Importance : 358 p. ISBN/ISSN/EAN : 978-3-030-01279-3 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] analyse de données [Termes IGN] données qualitatives [Termes IGN] Excel (logiciel) [Termes IGN] inférence statistique [Termes IGN] méthode de Monte-Carlo [Termes IGN] programmation linéaire Résumé : (Editeur) This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations. Note de contenu : 1. Introduction to Spreadsheet Modeling 2. Presentation of Quantitative Data: Data Visualization 3. Analysis of Quantitative Data 4. Presentation of Qualitative Data—Data Visualization 5. Analysis of Qualitative Data 6. Inferential Statistical Analysis of Data 7. Modeling and Simulation: Part 1 8. Modeling and Simulation: Part 2 9. Solver, Scenarios, and Goal Seek Tools Numéro de notice : 26280 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Manuel informatique DOI : 10.1007/978-3-030-01279-3 En ligne : https://doi.org/10.1007/978-3-030-01279-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94931

Towards qualitative geovisual analytics: A case study involving places, people, and mediated experience / Ryan Burns in Cartographica, vol 48 n° 3 (October 2013)  

Public [article]  inCartographica > vol 48 n° 3 (October 2013) . - pp 157 - 176 Titre : Towards qualitative geovisual analytics: A case study involving places, people, and mediated experience Type de document : Article/Communication Auteurs : Ryan Burns, Auteur ; André Skupin, Auteur Année de publication : 2013 Article en page(s) : pp 157 - 176 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] analyse visuelle [Termes IGN] carte de Kohonen [Termes IGN] données qualitatives [Termes IGN] retour d'expérience [Termes IGN] système d'information géographique [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) This article seeks to address the gap between the quantitative, summative data that are typically engaged in geovisual analytics and the more personal, experiential ways of knowledge construction accentuated by qualitative GIS. By incorporating diverse forms of data within a high-dimensional conceptual framework, we set out a type of qualitative geovisual analytics. This approach is attentive to the epistemological limitations of singular data sources and highlights the multiple ways of exploring neighbourhoods. The article reports on a project that used an online survey, including collection of personal impressions of San Diego neighbourhoods based on street-level video. Three attribute spaces are conceptualized: survey respondents' characteristics, attributes of San Diego neighbourhoods, and characteristics of the words used to describe these neighbourhoods. The self-organizing map (SOM) technique was used to reduce the dimensionality of these attribute spaces for visual exploration. This approach makes several important contributions, including a demonstration of “scaling up” the work that has been done in qualitative GIS. It productively integrates experiential data with a geovisual analytics approach and reaffirms the multiple meanings of visualization. Numéro de notice : A2013-570 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.3138/carto.48.3.1691 En ligne : https://doi.org/10.3138/carto.48.3.1691 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32706 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-2013031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Extending the qualitative capabilities of GIS : Computer-Aided Qualitative GIS / J. Jung in Transactions in GIS, vol 14 n° 1 (February 2010)  

Public [article]  inTransactions in GIS > vol 14 n° 1 (February 2010) . - pp 63 - 87 Titre : Extending the qualitative capabilities of GIS : Computer-Aided Qualitative GIS Type de document : Article/Communication Auteurs : J. Jung, Auteur ; S. Elwood, Auteur Année de publication : 2010 Article en page(s) : pp 63 - 87 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] analyse de données [Termes IGN] données qualitatives [Termes IGN] logiciel d'analyse de données [Termes IGN] qualité du processus [Termes IGN] système d'information géographique [Termes IGN] visualisation de données Résumé : (Auteur) A number of approaches for integrating GIS and qualitative research have emerged in recent years, as part of a resurgence of interest in mixed methods research in geography. These efforts to integrate qualitative data and qualitative analysis techniques complement a longstanding focus in GIScience upon ways of handling qualitative forms of spatial data and reasoning in digital environments, and extend engagements with 'the qualitative' in GIScience to include discussions of research methodologies. This article contributes to these emerging qualitative GIS methodologies by describing the structures and functions of 'computer-aided qualitative GIS' (CAQ-GIS), an approach for storing and analyzing qualitative, quantitative, and geovisual data in both GIS and computer aided data analysis software. CAQ-GIS uses modified structures from conventional desktop GIS to support storage of qualitative data and analytical codes, together with a parallel coding and analysis process carried out with GIS and a computer-aided data analysis software package. The inductive mixed methods analysis potential of CAQ-GIS is demonstrated with examples from research on children's urban geographies. Copyright Blackwell Publishing Numéro de notice : A2010-005 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2009.01182.x Date de publication en ligne : 17/01/2010 En ligne : https://doi.org/10.1111/j.1467-9671.2009.01182.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30201 [article]