Technical Program

Session Detail

Session Title FRP1.PI: Image Segmentation I
Presentation Mode Poster
Session Time Friday, 02 August, 09:40 - 10:40
Location Room 501-502: Poster Area I
Session ChairSebastiano Serpico, University of Genoa

FRP1.PI.1: TOWARDS AUTOMATED DELINEATION OF SMALLHOLDER FARM FIELDS FROM VHR IMAGES USING CONVOLUTIONAL NETWORKS
         Claudio Persello; University of Twente
         Valentyn Tolpekin; University of Twente
         John Ray Bergado; University of Twente
         Rolf de By; University of Twente

FRP1.PI.2: SEA-LAND SEGMENTATION WITH RES-UNET AND FULLY CONNECTED CRF
         Zhengquan Chu; China University of Geosciences
         Tian Tian; China University of Geosciences
         Ruyi Feng; China University of Geosciences
         Lizhe Wang; China University of Geosciences

FRP1.PI.3: THE MODIFIED ENCODER-DECODER NETWORK BASED ON DEPTHWISE SEPARABLE CONVOLUTION FOR WATER SEGMENTATION OF REAL SAR IMAGERY
         Jinsong Zhang; Xidian University
         Mengdao Xing; Xidian University
         Guangcai Sun; Xidian University

FRP1.PI.4: AN EFFECTIVE VARIATIONAL WATERLINE SEGMENTATION METHOD
         Yong Meng; National University of Defense Technology
         Zeming Zhou; National University of Defense Technology
         Yudi Liu; National University of Defense Technology
         Qixiang Luo; National University of Defense Technology
         Chenjing Tian; National University of Defense Technology
         Xiaofeng Zhao; National University of Defense Technology

FRP1.PI.5: A MARKOV RANDOM FIELD MOEL WITH ALTERNATING GRANULARITIES FOR SEGMENTATION OF HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGERY
         Chen Zheng; Henan University
         Min Zhang; Henan University
         Xiaohui Chen; Henan University
         Leiguang Wang; Southwest Forestry University

FRP1.PI.6: SEMANTIC SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGE BASED ON BATCH-ATTENTION MECHANISM
         Yanzhou Su; University of Electronic Science and Technology of China
         Yongjian Wu; Northeastern University
         Min Wang; University of Electronic Science and Technology of China
         Feng Wang; University of Electronic Science and Technology of China
         Jian Cheng; University of Electronic Science and Technology of China

FRP1.PI.7: SIMULTANEOUS SEGMENTATION AND EDGE DETECTION FOR HYPERSPECTRAL IMAGE VIA A DEEP SUPERVISED AND BOUNDARY-CONSTRAINED NETWORK
         Yonghao Xu; Wuhan University
         Bo Du; Wuhan University
         Liangpei Zhang; Wuhan University

FRP1.PI.8: FULL-RESOLUTION IMAGE SEGMENTATION MODEL COMBINING MULTI-SOURCE INPUT INFORMATION
         Chenxiao Feng; Shaanxi Normal University
         Xili Wang; Shaanxi Normal University
         Xiyuan Wang; Ningxia University
         Ming Liu; Shaanxi Normal University
         Jie Wu; Shaanxi Normal University

FRP1.PI.9: REGION-BASED IMAGE-KEY-ELEMENT DECOMPOSITION FOR LARGE-SCALE SAR IMAGES
         Weike Li; Harbin Institute of Technology
         Bin Zou; Harbin Institute of Technology
         Lamei Zhang; Harbin Institute of Technology
         Yu Xin; Beijing Institute of Remote Sensing Information

FRP1.PI.10: SEGMENTATION OF SENTINEL-2 IMAGES ON SNAP - AN EVALUATION WITH SITEF
         Andre R S Marcal; Faculdade de Ciencias, Universidade do Porto

FRP1.PI.11: A SIMPLE ROTATIONAL EQUIVARIANCE LOSS FOR GENERIC CONVOLUTIONAL SEGMENTATION NETWORKS: PRELIMINARY RESULTS
         Kangcheng Lin; Duke University
         Bohao Huang; Duke University
         Leslie Collins; Duke University
         Kyle Bradbury; Energy Initiative, Duke University
         Jordan Malof; Duke University

FRP1.PI.12: PIPELINE SEGMENTATION USING LEVEL-SET METHOD
         Apinya Leangaramkul; Kasetsart University
         Teerasit Kasetkasem; Kasetsart University
         Yodyium Tipsuwan; Kasetsart University
         Tsuyoshi Isshiki; Tokyo Institute of Technology
         Thitiporn Chanwimaluang; National Electronics and Computer Technology Center (NECTEC)
         Phakhachon Hoonsuwan; PTT Exploration and Production Public Company Limited (PTTEP)