FR2.R2.8

HLS-BASED FPGA IMPLEMENTATION OF CONVOLUTIONAL DEEP BELIEF NETWORK FOR SIGNAL MODULATION RECOGNITION

Jian Zhao, Yaqin Zhao, Hongbo Li, Yun Zhang, Longwen Wu, Harbin Institute of Technology, China

Session:
Machine Learning and Artificial Intelligence for Remote Sensing

Track:
Special Themes

Presentation Time:
Fri, 2 Oct, 15:40-15:50 (UTC)
Fri, 2 Oct, 23:40-23:50 China Standard Time (UTC +8)
Fri, 2 Oct, 17:40-17:50 Central Europe Summer Time (UTC +2)
Fri, 2 Oct, 08:40-08:50 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Gulsen Taskin, Istanbul Technical University and Xiao Xiang Zhu, German Aerospace Center (DLR)
Session Managers:
Subhadip Dey and Damilola Oladeji

Presentation

Discussion

Resources

Session

FR2.R2.1: IMPROVED GENETIC ALGORITHM FOR BUNDLE ADJUSTMENT IN PHOTOGRAMMETRY
Zhengkang Zuo, Yiyuan Sun, Ruihua Zhang, Lei Yan, Peking University, China
FR2.R2.2: SATELLITE OBSERVATION OF TANSMERIDIONAL PROPAGATING INTERNAL WAVES IN THE CELEBES SEA
Xudong Zhang, Institute of Oceanology, Chinese Academy of Sciences, China; Tao Zhang, Shandong University of Science and Technology; Institute of Oceanology, Chinese Academy of Sciences, China; Xiaofeng Li, Institute of Oceanology, Chinese Academy of Sciences, United States
FR2.R2.3: SPATIAL RESOLUTION ENHANCEMENT OF UNMANNED AIRCRAFT SYSTEM IMAGERY USING DEEP LEARNING-BASED SINGLE IMAGE SUPER-RESOLUTION
Mohammad Pashaei, Michael J. Starek, Hamid Kamangir, Jacob Berryhill, Texas A&M University-Corpus Christi, United States
FR2.R2.4: Edge Prediction Net for Reconstructing Road Labels Contaminated by Clouds
Miao Xu, Yuanxiang Li, Shanghai Jiao Tong University, China; Juanjuan Zhong, AVIC Leihua Electric Technology Research Institute, China; Yuxuan Zhang, Shanghai Jiao Tong University, China; Xingang Liu, AVIC Leihua Electric Technology Research Institute, China
FR2.R2.5: MINERAL DETECTION FROM HYPERSPECTRAL IMAGES USING A SPATIAL-SPECTRAL RESIDUAL CONVOLUTIONAL NEURAL NETWORK
Hao Zeng, Qingjie Liu, Beihang University, China; Xiaoqing Han, Beijing Research Institute of Uranium Geology, China; Yunhong Wang, Beihang University, China
FR2.R2.6: RADIO-FREQUENCY INTERFERENCE LOCATION, DETECTION AND CLASSIFICATION USING DEEP NEURAL NETWORKS
Adrian Perez, Universitat Politècnica de Catalunya (UPC), Spain; Jorge Querol, University of Luxembourg, Luxembourg; Hyuk Park, Adriano Camps, Universitat Politècnica de Catalunya (UPC), Spain
FR2.R2.7: UNBALANCED GEOLOGIC BODY CLASSIFICATION OF HYPERSPECTRAL DATA BASED ON SQUEEZE AND EXCITATION NETWORKS AT TIANSHAN AREA
Yuchen Liang, Zhengang Zhao, Hao Wang, Beijing Normal University, China; Ying Cao, Beijing Institute of Geology, China; Tao Huang, Yasmine Medjadba, Beijing Normal University, China; Yuntao Wang, RunCheng Jiao, Beijing Institute of Geology, China; Siying Chen, Xianchuan Yu, Beijing Normal University, China
FR2.R2.8: HLS-BASED FPGA IMPLEMENTATION OF CONVOLUTIONAL DEEP BELIEF NETWORK FOR SIGNAL MODULATION RECOGNITION
Jian Zhao, Yaqin Zhao, Hongbo Li, Yun Zhang, Longwen Wu, Harbin Institute of Technology, China
FR2.R2.9: CORRELATION ATTENTION FOR REMOTE SENSING IMAGE CAPTIONING
Jingxian Tian, Shuang Wang, Yu Gu, Yun Meng, Xiutiao Ye, Lei Zhang, Jihui Wang, Biao Hou, Xidian University, China
FR2.R2.10: RTC-GAN: Real-Time Classification of Satellite Imagery using Deep Generative Adversarial Networks with Infused Spectral Information
Rohit Gandikota, Radha Krishna Kavluru, Anupama Sharma, ManjuSarma M, Vinod M Bothale, National Remote Sensing Center, Indian Space Research Organisation, India
FR2.R2.11: A METHOD TO CREATE TRAINING DATASET FOR DEHAZING WITH CYCLEGAN
Hui Zhang, Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd, China; Fan Mou, University of Electronic Science and Technology of China, China; Shangqi Duan, Shuangde Huang, Shengwei Wang, Debin Xu, Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd, China; Zezhong Zheng, University of Electronic Science and Technology of China, China
FR2.R2.12: RADAR SENSOR SIMULATION WITH GENERATIVE ADVERSARIAL NETWORK
Maryam Rahnemoonfar, Masoud Yari, University of Maryland, Baltimore County, United States; John Paden, University of Kansas, United States