Session Title | MOP2.PD: Deep Learning for Object Detection I |
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Presentation Mode | Poster |
Session Time | Monday, 29 July, 15:20 - 16:20 |
Location | Room 501-502: Poster Area D |
Session Chair | Haipeng Wang, Fudan University |
MOP2.PD.1: COMBINED CONVOLUTIONAL AND STRUCTURED FEATURES FOR POWER LINE DETECTION IN UAV IMAGES |
Heng Zhang; Wuhan University |
Wen Yang; Wuhan University |
Huai Yu; Wuhan University |
Fang Xu; Wuhan University |
Haijian Zhang; Wuhan University |
MOP2.PD.2: PIXELWISE REMOTE SENSING IMAGE CLASSIFICATION BASED ON RECURRENCE PLOT DEEP FEATURES |
Danielle Dias; Unicamp |
Ulisses Dias; Unicamp |
Nathalia Menini; Unicamp |
Rubens Lamparelli; Unicamp |
Guerric Le Maire; Univ. Montpellier |
Ricardo Torres; Unicamp |
MOP2.PD.3: ROBUST REAL-TIME OBJECT DETECTION BASED ON DEEP LEARNING FOR VERY HIGH RESOLUTION REMOTE SENSING IMAGES |
Yiming Zhao; Beijing University of Posts and Telecommunications |
Jinzheng Zhao; Beijing University of Posts and Telecommunications |
Chunyu Zhao; Beijing University of Posts and Telecommunications |
Weiyu Xiong; Beijing University of Posts and Telecommunications |
Qingli Li; Beijing University of Posts and Telecommunications |
Junli Yang; Beijing University of Posts and Telecommunications |
MOP2.PD.4: A WEAKLY-SUPERVISED DEEP NETWORK FOR DSM-AIDED VEHICLE DETECTION |
Xin Wu; Beijing Institute of Technology |
Danfeng Hong; German Aerospace Center (DLR) / Technical University of Munich (TUM) |
Jiaojiao Tian; German Aerospace Center (DLR) |
Ralph Kiefl; German Aerospace Center (DLR) |
Ran Tao; Beijing Institute of Technology |
MOP2.PD.5: AN IMPROVED FASTER R-CNN BASED ON MSER DECISION CRITERION FOR SAR IMAGE SHIP DETECTION IN HARBOR |
Rufei Wang; University of Electronic Science and Technology of China |
Fanyun Xu; University of Electronic Science and Technology of China |
Jifang Pei; University of Electronic Science and Technology of China |
Chenwei Wang; University of Electronic Science and Technology of China |
Yulin Huang; University of Electronic Science and Technology of China |
Jianyu Yang; University of Electronic Science and Technology of China |
Junjie Wu; University of Electronic Science and Technology of China |
MOP2.PD.6: COMPARISON OF DEEP LEARNING MODEL PERFORMANCE BETWEEN META-DATASET TRAINING VERSUS DEEP NEURAL ENSEMBLES |
Alex Hurt; University of Missouri |
Grant Scott; University of Missouri |
Curt Davis; University of Missouri |
MOP2.PD.7: GLOBAL RECEPTIVE BASED NEURAL NETWORK ORIENTED TO TARGET RECOGNITION IN SAR IMAGES |
Ganggang Dong; Xidian University |
Hongwei Liu; Xidian University |
MOP2.PD.8: T-SCNN: A TWO-STAGE CONVOLUTIONAL NEURAL NETWORK FOR SPACE TARGET RECOGNITION |
Tan Wu; Xidian University |
Xi Yang; Xidian University |
Bin Song; Xidian University |
Nannan Wang; Xidian University |
Xinbo Gao; Xidian University |
Liyang Kuang; Xidian University |
Xiaoting Nan; Xidian University |
Yuwen Chen; Xidian University |
Dong Yang; Xi’an Institute of Space Radio Technology |
MOP2.PD.9: CLASS-ORIENTED LOCAL STRUCTURE PRESERVING DICTIONARY LEARNING FOR SAR TARGET RECOGNITION |
Haohao Ren; University of Electronic Science and Technology of China |
Xuelian Yu; University of Electronic Science and Technology of China |
Lin Zou; University of Electronic Science and Technology of China |
Yun Zhou; University of Electronic Science and Technology of China |
Xuegang Wang; University of Electronic Science and Technology of China |
MOP2.PD.10: SIAMESE NETWORK BASED METRIC LEARNING FOR SAR TARGET CLASSIFICATION |
Zongxu Pan; Institute of Electronics, Chinese Academy of Sciences |
Xianjie Bao; Institute of Electronics, Chinese Academy of Sciences |
Yueting Zhang; Institute of Electronics, Chinese Academy of Sciences |
Bowei Wang; Institute of Electronics, Chinese Academy of Sciences |
Quanzhi An; Institute of Electronics, Chinese Academy of Sciences |
Bin Lei; Institute of Electronics, Chinese Academy of Sciences |
MOP2.PD.11: ATTENTION BASED RESIDUAL NETWORK FOR HIGH-RESOLUTION REMOTE SENSING IMAGERY SCENE CLASSIFICATION |
Runyu Fan; China University of Geosciences |
Lizhe Wang; China University of Geosciences |
Ruyi Feng; China University of Geosciences |
Yingqian Zhu; China University of Geosciences |