MO1.R1.4

CONVOLUTIONAL AUTOENCODER MODEL FOR HYPERSPECTRAL MULTI-SENSOR SATELLITE DATA COMPRESSION

Jannick Kuester, Wolfgang Gross, Simon Schreiner, Wolfgang Middelmann, Fraunhofer IOSB, Germany; Michael Heizmann, Karlsruhe Institute of Technology, Germany
Session:
MO1.R1: Deep Learning for Image Processing Oral
Track:
Data Analysis
Location:
Room B
Presentation Time:
Mon, 17 Jul, 13:36 - 13:48 Pacific Time (UTC -7)
Session Chair:
Jannick Kuester, Fraunhofer IOSB
Session Manager:
Shubham Awasthi
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Session MO1.R1
MO1.R1.1: DESPECKLING OF SAR IMAGES USING CNN AND MULTIRESOLUTION FUSION
Dusan Gleich, Primoz Smogavec, University of Maribor, Slovenia
MO1.R1.2: NEAR-FIELD SAR IMAGE RESTORATION FRAMEWORK VIA DEEP LEARNING
Wensi Zhang, Xiaoling Zhang, Jun Shi, Shunjun Wei, Tianjiao Zeng, University of Electronic Science and Technology of China, China
MO1.R1.3: HIERARCHICAL SUPERPIXEL RELATION GRAPH COMBINED WITH CONVOLUTIONAL SPARSE CODING FOR SELF-SUPERVISED HYPERSPECTRAL IMAGE DENOISING
Zhongshun Jiang, Zhejiang University, China; Qipeng Qian, University of Arizona, United States; Yi Qiu, Huzhou University, China; Yuntao Qian, Zhejiang University, China
MO1.R1.4: CONVOLUTIONAL AUTOENCODER MODEL FOR HYPERSPECTRAL MULTI-SENSOR SATELLITE DATA COMPRESSION
Jannick Kuester, Wolfgang Gross, Simon Schreiner, Wolfgang Middelmann, Fraunhofer IOSB, Germany; Michael Heizmann, Karlsruhe Institute of Technology, Germany
Resources
No resources available.