July 28 - August 2, 2019 • Yokohama, Japan

Pacifico Yokohama

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Session Detail

Session Title MOP2.PD: Deep Learning for Object Detection I
Presentation Mode Poster
Session Time Monday, 29 July, 15:20 - 16:20
Location Room 501-502: Poster Area D
Session ChairHaipeng 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