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MOP2.PG: Applications of Deep Learning

Session Type: Poster

Time: Monday, July 23, 15:50 - 16:50

Location: Poster Area G

Session Chairs: Emanuele Santi, CNR-IFAC and Xuiping Jia, University of New South Wales at Canberra

MOP2.PG.1: OIL-PALM TREE DETECTION IN AERIAL IMAGES COMBINING DEEP LEARNING CLASSIFIERS

Maciel Zortea; IBM Research

Marcelo Nery; IBM Research

Bernardo Ruga; IBM Research

Lara Bispo Carvalho; Agropalma

Adriano Chaves Bastos; Agropalma

MOP2.PG.2: SPECTRAL-SPATIAL TOPOGRAPHIC SHADOW DETECTION FROM SENTINEL-2A MSI IMAGERY VIA CONVOLUTIONAL NEURAL NETWORKS

Hui Huang; China University of Petroleum (East China)

Genyun Sun; China University of Petroleum (East China)

Jinchang Ren; University of Strathclyde

Jun Rong; China University of Petroleum (East China)

Aizhu Zhang; China University of Petroleum (East China)

Yanling Hao; China University of Petroleum (East China)

MOP2.PG.3: AGGREGATING DEEP CONVOLUTIONAL NEURAL NETWORK SCANS OF BROAD-AREA HIGH-RESOLUTION REMOTE SENSING IMAGERY

Grant Scott; University of Missouri

Alex Hurt; University of Missouri

Richard Marcum; University of Missouri

Derek Anderson; University of Missouri

Curt Davis; University of Missouri

MOP2.PG.4: AN ADAPTATION OF CNN FOR SMALL TARGET DETECTION IN THE INFRARED

Dong Zhao; Xidian University

Huixin Zhou; Xidian University

Shenghui Rong; Xidian University

Xiuping Jia; University of New South Wales

MOP2.PG.5: ROTATED REGION BASED FULLY CONVOLUTIONAL NETWORK FOR SHIP DETECTION

Mingjie Li; Shanghai Jiao Tong University

Weiwei Guo; Shanghai Jiao Tong University

Zenghui Zhang; Shanghai Jiao Tong University

Wenxian Yu; Shanghai Jiao Tong University

Tao Zhang; Shanghai Jiao Tong University

MOP2.PG.6: A TRANSLATIONAL INVARIANT SAR-ATR METHOD BASED ON CONVOLUTIONAL NEURAL NETWORKS

Zongyong Cui; University of Electronic Science and Technology of China

Sifei Wang; University of Electronic Science and Technology of China

Sihang Dang; University of Electronic Science and Technology of China

Zongjie Cao; University of Electronic Science and Technology of China

MOP2.PG.7: SHIP DETECTION BASED ON DEEP CONVOLUTIONAL NEURAL NETWORKS FOR POLSAR IMAGES

Feng Zhou; Xidian University

Weiwei Fan; Xidian University

Qiangqiang Sheng; Xidian University

Mingliang Tao; Northwestern Polytechnical University

MOP2.PG.8: NARROW ROAD EXTRACTION FROM REMOTE SENSING IMAGES BASED ON SUPER-RESOLUTION CONVOLUTIONAL NEURAL NETWORK

Xinyu Zhou; Harbin Institute of Technology

Xi Chen; Key Laboratory of Geographic Information Science (Ministry of Education)

Ye Zhang; Harbin Institute of Technology

MOP2.PG.9: DATA AUGMENTATION WITH GABOR FILTER IN DEEP CONVOLUTIONAL NEURAL NETWORKS FOR SAR TARGET RECOGNITION

Ting Jiang; University of Electronic Science and Technology of China

Zongyong Cui; University of Electronic Science and Technology of China

Zhi Zhou; University of Electronic Science and Technology of China

Zongjie Cao; University of Electronic Science and Technology of China

MOP2.PG.10: INSHORE SHIP DETECTION BASED ON MASK R-CNN

Shanlan Nie; Beihang University

Zhiguo Jiang; Beihang University

Haopeng Zhang; Beihang University

Bowen Cai; Beihang University

Yuan Yao; Beihang University