TH1.R17.5

PYRAMID CONVOLUTIONAL NEURAL NETWORKS AND BOTTLENECK RESIDUAL MODULES FOR CLASSIFICATION OF MULTISPECTRAL IMAGES

Yukun Huang, Jiangxi University of Finance and Economics, China; Jingbo Wei, Wenchao Tang, Chaoqi He, Nanchang University, China

Session:
Learning and Adaptive Methods for Image Clustering

Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

Presentation Time:
Thu, 1 Oct, 12:40-12:50 (UTC)
Thu, 1 Oct, 20:40-20:50 China Standard Time (UTC +8)
Thu, 1 Oct, 14:40-14:50 Central Europe Summer Time (UTC +2)
Thu, 1 Oct, 05:40-05:50 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Xudong Kang, Hunan University and Thales Körting, INPE
Session Managers:
Ahmed Balakhder and Genc Hoxha

Presentation

Discussion

Resources

Session

TH1.R17.1: PATCH BASED LAND COVER CLASSIFICATION: A COMPARISON OF DEEP LEARNING, SVM AND NN CLASSIFIERS
Mahesh Pal, Akshay Poriya, Himanshu Rohilla, B. Charan Teja, National Institute of Technology, Kurukshetra, India
TH1.R17.2: A LEARNABLE BLUR KERNEL FOR REMOTE SENSING IMAGE RETRIEVAL
Zelin Peng, Guanchun Wang, Xiangrong Zhang, Xu Tang, Xidian University, China; Li Gao, State Key Laboratory of Geo-information Engineering, China; Licheng Jiao, Xidian University, China
TH1.R17.3: INTEGRATION OF SENTINEL 1 AND 2 OBSERVATIONS FOR MAPPING EARLY AND LATE SOWING OF SOYBEAN AND COTTON CROP USING DEEP LEARNING
Jayantrao Mohite, Suryakant Sawant, Ankur Pandit, Srinivasu Pappula, Tata Consultancy Services, India
TH1.R17.4: END-TO-END DEEP LEARNING SEMANTIC CLASSIFICATION ARCHITECTURE FOR REMOTE SENSING IMAGERY
Haiyan Gu, Yi Yang, Yanshun Han, Haitao Li, Chinese Academy of Surveying and Mapping, China; Ying Tang, Lanzhou Jiaotong University, China
TH1.R17.5: PYRAMID CONVOLUTIONAL NEURAL NETWORKS AND BOTTLENECK RESIDUAL MODULES FOR CLASSIFICATION OF MULTISPECTRAL IMAGES
Yukun Huang, Jiangxi University of Finance and Economics, China; Jingbo Wei, Wenchao Tang, Chaoqi He, Nanchang University, China
TH1.R17.6: SAMPLING SUBJECTIVE POLYGONS FOR PATCH-BASED DEEP LEARNING LAND-USE CLASSIFICATION IN SATELLITE IMAGES
Jacob Arndt, Dalton Lunga, Oak Ridge National Laboratory, United States
TH1.R17.7: SIMILAR REGION RECOMMENDATION BASED ON HISTOGRAM FEATURES
Qiankun Liu, Qiang Liu, Dingyou Xu, Jing He, Yukun Mao, University of Electronic Science and Technology of China, China
TH1.R17.8: A CYCLE GAN APPROACH FOR HETEROGENEOUS DOMAIN ADAPTATION IN LAND USE CLASSIFICATION
Claire Voreiter, Jean-Christophe Burnel, Université Bretagne Sud, France; Pierre Lassalle, Centre National d'Etudes Spatiales (CNES), France; Marc Spigai, Romain Hugues, Thales Alenia Space, France; Nicolas Courty, Université Bretagne Sud, France
TH1.R17.9: FROM SUPERVISED TO UNSUPERVISED LEARNING FOR LAND COVER ANALYSIS OF SENTINEL-2 MULTISPECTRAL IMAGES.
Jayasree Saha, Yuvraj Khanna, Jayanta Mukhopadhyay, Subhas Aikat, Indian Institute of Technology Kharagpur, India
TH1.R17.10: Deep Convolutional Neural Network for Mangrove Mapping
Corina Iovan, Michel Kulbicki, Institut de Recherche pour le Developpement, France; Eric Mermet, École des hautes études en sciences sociales, France
TH1.R17.11: APPROACHING REMOTE SENSING IMAGE CLASSIFICATION WITH ENSEMBLES OF SUPPORT VECTOR MACHINES ON THE D-WAVE QUANTUM ANNEALER
Gabriele Cavallaro, Dennis Willsch, Madita Willsch, Kristel Michielsen, Morris Riedel, Forschungszentrum Jülich, Germany