Technical Program

Session Detail

Session Title WEP2.PO: Big Data and Machine Learning - Neural Network in Remote Sensing I
Presentation Mode Poster
Session Time Wednesday, 31 July, 15:20 - 16:20
Location Room 501-502: Poster Area O
Session ChairAkira Iwasaki, University of Tokyo

WEP2.PO.1: WEED MAPPING USING VERY HIGH RESOLUTION SATELLITE IMAGERY AND FULLY CONVOLUTIONAL NEURAL NETWORK
         Yannik Rist; CSIRO
         Iurii Shendryk; CSIRO
         Foivos Diakogiannis; CSIRO
         Shaun Levick; CSIRO

WEP2.PO.2: DEEP CONVOLUTIONAL NEURAL NETWORKS FOR PLANE IDENTIFICATION ON SATELLITE IMAGERY BY EXPLOITING TRANSFER LEARNING WITH A DIFFERENT OPTIMIZER
         Patcharin Kamsing; King Mongkut’s Institute of Technology Ladkrabang
         Peerapong Torteeka; National Astronomical Research Institute of Thailand
         Soemsak Yooyen; King Mongkut’s Institute of Technology Ladkrabang

WEP2.PO.3: SEMI-SUPERVISED VARIATIONAL GENERATIVE ADVERSARIAL NETWORKS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Hao Wang; Central South University
         Chao Tao; Central South University
         Ji Qi; Central South University
         HaiFeng Li; Central South University
         YuQi Tang; Central South University

WEP2.PO.4: P-WAVE IDENTIFICATION WITH DEEP NEURAL NETWORK
         Wei Zhu; Northwest Institute of Nuclear Technology
         Xin Li; Northwest Institute of Nuclear Technology
         Chang Liu; Northwest Institute of Nuclear Technology
         Xiong Xu; Northwest Institute of Nuclear Technology
         Weiping Ni; Northwest Institute of Nuclear Technology

WEP2.PO.5: DEEP LEARNING ROAD EXTRACTION MODEL BASED ON SIMILARITY MAPPING RELATIONSHIP
         Haoyu Li; University of Electronic Science and Technology of China
         Yunping Chen; University of Electronic Science and Technology of China
         Yue Yang; University of Electronic Science and Technology of China
         Peixin Liu; University of Electronic Science and Technology of China
         Chuanqi Zhong; University of Electronic Science and Technology of China

WEP2.PO.6: AERIAL IMAGE AND MAP SYNTHESIS USING GENERATIVE ADVERSARIAL NETWORKS
         Jun Gu; Institute of Electronics, Chinese Academy of Sciences
         Yue Zhang; Institute of Electronics, Chinese Academy of Sciences
         Wenkai Zhang; Institute of Electronics, Chinese Academy of Sciences
         Hongfeng Yu; Institute of Electronics, Chinese Academy of Sciences
         Siyue Wang; Northeastern University
         Yaoling Wang; Institute of Electronics, Chinese Academy of Sciences
         Lei Wang; Institute of Electronics, Chinese Academy of Sciences

WEP2.PO.7: A DEEP LEARNING ARCHITECTURE FOR HETEROGENEOUS AND IRREGULARLY SAMPLED REMOTE SENSING TIME SERIES
         Corrado Avolio; e-GEOS - Italian Space Agency / Telespazio
         Alessia Tricomi; e-GEOS - Italian Space Agency / Telespazio
         Claudio Mammone; e-GEOS - Italian Space Agency / Telespazio
         Massimo Zavagli; e-GEOS - Italian Space Agency / Telespazio
         Mario Costantini; e-GEOS - Italian Space Agency / Telespazio

WEP2.PO.8: IMPROVED SEARCH AND DETECTION OF SURFACE-TO-AIR MISSILE SITES USING SPATIAL FUSION OF COMPONENT OBJECT DETECTIONS FROM DEEP NEURAL NETWORKS
         Alan Cannaday; University of Missouri
         Curt Davis; University of Missouri
         Grant Scott; University of Missouri

WEP2.PO.9: AN EXTENSIBLE AND EASY-TO-USE TOOLBOX FOR DEEP LEARNING BASED ANALYSIS OF REMOTE SENSING IMAGES
         Raian Vargas Maretto; National Institute for Space Research (INPE)
         Thales Sehn Körting; National Institute for Space Research (INPE)
         Leila Maria Garcia Fonseca; National Institute for Space Research (INPE)