FR2.R16.7

SHIP DETECTION AND FINE-GRAINED RECOGNITION IN LARGE-FORMAT REMOTE SENSING IMAGES BASED ON CONVOLUTIONAL NEURAL NETWORK

Jingrun Li, Jinwen Tian, Peng Gao, Linfeng Li, School of Artificial Intelligence and Automation, Huazhong University of Science Technology, China

Session:
Enhancement Methods for Image Analysis

Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

Presentation Time:
Fri, 2 Oct, 15:30-15:40 (UTC)
Fri, 2 Oct, 23:30-23:40 China Standard Time (UTC +8)
Fri, 2 Oct, 17:30-17:40 Central Europe Summer Time (UTC +2)
Fri, 2 Oct, 08:30-08:40 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Dušan Gleich, University of Maribor and Sylvain Lobry, Université de Paris
Session Managers:
Manap Shymyr and Shashank S. Joshil

Presentation

Discussion

Resources

Session

FR2.R16.1: DATA ADAPTIVE IMAGE ENHANCEMENT AND CLASSIFICATION FOR SYNTHETIC APERTURE SONAR
Isaac Gerg, Pennsylvania State University, United States; David Williams, Centre for Maritime Research and Experimentation, Italy; Vishal Monga, Pennsylvania State University, United States
FR2.R16.2: Deep Learning for Automatic Recognition of Oil Production Related Objects based on High-Resolution Remote Sensing Imagery
Nannan Zhang, Hang Zhao, Research Institute of Petroleum Exploration & Development,Petrochina, China; Yang Liu, Song Liu, Zhiguo Ma, Hongyan Guo, Wentong Dong, Hongying Zhou, Zhongyong Sun, Kaijun Qian, Research Institute of Petroleum Exploration & Development, PetroChina, China
FR2.R16.3: ADAPTIVE FUSION AND MASK REFINEMENT INSTANCE SEGMENTATION NETWORK FOR HIGH RESOLUTION REMOTE SENSING IMAGES
Jie Ran, Feng Yang, Chenqiang Gao, Yue Zhao, Anyong Qin, Chongqing University of Posts and Telecommunications, China
FR2.R16.4: A NOVEL SUPPORT VECTOR MACHINE BASED RADAR INDIVIDUAL RECOGNITION ALGORITHM UNDER INCONSISTENT NOISE CONDITION
Jiayue Wu, Bin Wu, Haonan Niu, Congcong Ma, Zhao Wang, Peng Li, Xidian University, China
FR2.R16.5: DATA AUGMENTATION FOR SHIP DETECTION USING KOMPSAT-5 IMAGES AND DEEP LEARNING MODEL
Seung-Jae Lee, Jae-Young Chang, Kwang-Jae Lee, Kwan-Young Oh, Korea Aerospace Research Institute (KARI), Korea (South)
FR2.R16.6: ELLIPSE-FCN: OIL TANKS DETECTION FROM REMOTE SENSING IMAGES WITH FULLY CONVOLUTION NETWORK
Ziteng Cui, Shanghai Jiao Tong University, China; Weiwei Guo, Tongji University, China; Zenghui Zhang, Huiyuan Chen, Wenxian Yu, Shanghai Jiao Tong University, China
FR2.R16.7: SHIP DETECTION AND FINE-GRAINED RECOGNITION IN LARGE-FORMAT REMOTE SENSING IMAGES BASED ON CONVOLUTIONAL NEURAL NETWORK
Jingrun Li, Jinwen Tian, Peng Gao, Linfeng Li, School of Artificial Intelligence and Automation, Huazhong University of Science Technology, China
FR2.R16.8: SAR IMAGE SHIP DETECTION BASED ON SCENE INTERPRETATION
Shilong Hou, Xiaorui Ma, Dalian University of Technology, China; Xinrong Wang, Space Star Technology Co.Ltd, China; Zanhao Fu, Chongqing University, China; Jie Wang, Hongyu Wang, Dalian University of Technology, China
FR2.R16.9: IMAGE CLASSIFICATION IN SYNTHETIC APERTURE RADAR USING RECONSTRUCTION FROM LEARNED INVERSE SCATTERING
Jacqueline Alvarez, Omar DeGuchy, Roummel Marcia, University of California, Merced, United States
FR2.R16.10: A DETECTION METHOD OF MULTI-SENSOR FOR RADAR COUNTERMEASURE NETWORK
Yanli Tang, Tao Wan, Kaili Jiang, Ying Xiong, Bin Tang, University of Electronic Science and Technology of China, China
FR2.R16.11: VIZUALIZATION OF SAR CATEGORIES USING COMPLEX VALUED DEEP LEARNING
Dušan Gleich, University of Maribor, Slovenia