IEEE IGARSS 2020 || Virtual Symposium || September 26 - October 2, 2020

FR1.R2.5

A DECEPTIVE JAMMING TEMPLATE SYNTHESIS METHOD FOR SAR USING GENERATIVE ADVERSARIAL NETS

Weiwei Fan, Feng Zhou, Tian Tian, Xidian University, China

Session:

Machine Learning for Earth Observation II

Track:

Special Themes

Presentation Time:

Fri, 2 Oct, 12:40-12:50 (UTC)
Fri, 2 Oct, 20:40-20:50 China Standard Time (UTC +8)
Fri, 2 Oct, 14:40-14:50 Central Europe Summer Time (UTC +2)
Fri, 2 Oct, 05:40-05:50 Pacific Daylight Time (UTC -7)

Session Co-Chairs:

Lexie Yang, Oak Ridge National Laboratory and Yuliya Tarabalka, LuxCarta

Session Managers:

Selena Chavez and Juan Carlos Hernandez Sanchez

Presentation

Discussion

Resources

Session

FR1.R2.1: CLASSIFYING GLOBAL LOW CLOUD MORPHOLOGY WITH A DEEP LEARNING MODEL: RESULTS AND POTENTIAL USE

Tianle Yuan, NASA GFSC / UMBC JCET, United States; Hua Song, NASA GFSC / SSAI, United States; John Mohrmann, Robert Wood, Univ. of Washington, United States; Kerry Meyer, Lazaros Oreopoulos, Steven Platnick, NASA Goddard Space Flight Center, United States

FR1.R2.2: DEEP RECURRENT NEURAL NETWORK FOR CROP CLASSIFICATION TASK BASED ON SENTINEL-1 AND SENTINEL-2 IMAGERY

Nataliia Kussul, Mykola Lavreniuk, Leonid Shumilo, Space Research Institute, Ukraine

FR1.R2.3: A FAST SEARCH SYSTEM FOR REMOTE SENSING IMAGERY BASED ON BAG OF VISUAL WORDS AND LATENT DIRICHLET ALLOCATION

Chandrabali Karmakar, Mihai Datcu, German Aerospace Center (DLR), Germany

FR1.R2.4: COMPLEXITY ANALYSIS OF AN EDGE PRESERVING CNN SAR DESPECKLING ALGORITHM

Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio, Università di Napoli Parthenope, Italy

FR1.R2.5: A DECEPTIVE JAMMING TEMPLATE SYNTHESIS METHOD FOR SAR USING GENERATIVE ADVERSARIAL NETS

Weiwei Fan, Feng Zhou, Tian Tian, Xidian University, China

FR1.R2.6: IDENTIFYING SEA ICE RIDGING IN SAR IMAGERY USING CONVOLUTIONAL NEURAL NETWORKS

Daniel Sola, Anmol Sharan Nagi, K Andrea Scott, University of Waterloo, Canada

FR1.R2.7: Multi-Scale and Temporal Transfer Learning for Automatic Tracking of Internal Ice Layers

Masoud Yari, Maryam Rahnemoonfar, University of Maryland, Baltimore County, United States; John Paden, Kansas University, United States

FR1.R2.8: THE SMART ICE CLOUD SENSING (SMICES) SMALLSAT CONCEPT

Xavier Bosch Lluis, Mehmet Ogut, Sidharth Misra, Pekka Kangaslahti, Jonathan Jiang, Erich Schlecht, NASA Jet Propulsion Laboratory, United States; William Deal, Northrop Grumman Corporation, United States

FR1.R2.9: SCHEDULING MISSION RECONFIGURATION FOR AN INTERFEROMETRY SYNTHETIC APERTURE RADAR USING DEEP REINFORCEMENT LEARNING

Antoni Viros-i-Martin, Daniel Selva, Texas A&M University, United States; Ryan Alimo, NASA Jet Propulsion Laboratory, California Institute of Technology, United States

FR1.R2.10: DATA MINING ON THE CANDELA CLOUD PLATFORM

Wei Yao, Octavian Dumitru, German Aerospace Center, Germany; Jose Lorenzo, ATOS SPAIN SA, Spain; Mihai Datcu, German Aerospace Center, Germany

FR1.R2.11: THE SMART ICE CLOUD SENSING (SMICES) SMALLSAT INSTRUMENT ARTIFICIAL INTELLIGENCE STRATEGIES

Mehmet Ogut, Xavier Bosch-Lluis, Sidharth Misra, Pekka Kangaslahti, Jonathan Jiang, Erich Schlecht, NASA Jet Propulsion Laboratory, California Institute of Technology, United States; William Deal, Kevin Leong, Caitlyn Cooke, Ken Kreischer, John Tucek, Northrop Grumman Corporation, United States

FR1.R2.12: PENALTY DRIVEN TRAINING SAMPLE REFINEMENT TECHNIQUE FOR HYPERSPECTRAL IMAGES CLASSIFICATION USING ANT COLONY OPTIMIZATION

Shakti Sharma, Bennett University, India