TH4.R10.3

HYSPECNET-11K: A LARGE-SCALE HYPERSPECTRAL DATASET FOR BENCHMARKING LEARNING-BASED HYPERSPECTRAL IMAGE COMPRESSION METHODS

Martin Hermann Paul Fuchs, Begüm Demir, Technische Universität Berlin, Germany
Session:
TH4.R10: AI-based Methods for EO Data Compression Oral
Track:
Community-Contributed Sessions
Location:
Room 101
Presentation Time:
Thu, 20 Jul, 16:09 - 16:21 Pacific Time (UTC -7)
Session Co-Chairs:
Paola Rizzoli, DLR and Mihai Ivanovici, Transilvania University of Brasov
Session Manager:
Ayoti Banerjee
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Session TH4.R10
TH4.R10.1: AI-BASED PERFORMANCE-OPTIMIZED QUANTIZATION FOR FUTURE SAR SYSTEMS
Nicola Gollin, Michele Martone, Gerhard Krieger, Paola Rizzoli, German Aerospace Center (DLR), Germany
TH4.R10.2: EXPONENTIAL FEATURE EXTRACTION AND LEARNING FOR PIXEL-WISE HYPERSPECTRAL IMAGE COMPRESSION
Mihai Ivanovici, Kamal Marandskiy, Transilvania University of Brasov, Romania
TH4.R10.3: HYSPECNET-11K: A LARGE-SCALE HYPERSPECTRAL DATASET FOR BENCHMARKING LEARNING-BASED HYPERSPECTRAL IMAGE COMPRESSION METHODS
Martin Hermann Paul Fuchs, Begüm Demir, Technische Universität Berlin, Germany
TH4.R10.4: ON-BOARD IMAGE COMPRESSION USING CONVOLUTIONAL AUTOENCODER: PERFORMANCE ANALYSIS AND APPLICATION SCENARIOS
Giorgia Guerrisi, Giovanni Schiavon, Fabio Del Frate, Tor Vergata University of Rome, Italy
TH4.R10.5: COMPLEX-VALUED AUTOENCODER FOR MULTI-POLARIZATION SLC SAR DATA COMPRESSION WITH SIDE INFORMATION
Reza Mohammadi Asiyabi, Andrei Anghel, University POLITEHNICA of Bucharest, Romania; Paola Rizzoli, Michele Martone, German Aerospace Center (DLR), Germany; Mihai Datcu, University POLITEHNICA of Bucharest, Romania
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