TU2.M3: Deep Learning Techniques for Image Classification I
Tuesday, 5 August, 10:30 - 11:45
Location: Mezzanine: Room M3
Session Type: Oral
Session Co-Chairs: Charlotte Pelletier , Univ. Bretagne Sud (UBS) and Francescopaolo Sica, University of the Bundeswehr Munich
Track: AI and Big Data
Tue, 5 Aug, 10:30 - 10:45

TU2.M3.1: Dilated-RNNs: A Deep Approach for Continuous Volcano-Seismic Events Recognition
Manuel Titos, Joe Carthy, Luz García, University of Granada, Spain; Talfan Barnei, Icelandic Meteo Office, Iceland; Carmen Benítez, University of Granada, Spain
Tue, 5 Aug, 10:45 - 11:00

TU2.M3.2: COMMUNICATION-EFFICIENT FEDERATED LEARNING BASED ON EXPLANATION-GUIDED PRUNING FOR REMOTE SENSING IMAGE CLASSIFICATION
Jonas Klotz, Barış Büyüktaş, Begüm Demir, Technische Universität Berlin / Berlin Institute for the Foundations of Learning and Data, Germany
Tue, 5 Aug, 11:00 - 11:15

TU2.M3.3: DYNAMIC LEARNING RATE FOR FEW-SHOT INCREMENTAL LEARNING IN OPTICAL REMOTE SENSING IMAGE CLASSIFICATION
Yihang Liu, Mingyang Ma, Zonghao Han, Zixiang Ye, Huiyang Han, Shaohui Mei, Northwestern Polytechnical University, China
Tue, 5 Aug, 11:15 - 11:30

TU2.M3.4: Multi-Scale Attention and Contrastive Learning for Signal Modulation Classification
Hongbo Li, Yongyu Ge, Feiyu Yu, Youjia Guo, Jian Zhao, Harbin Institute of Technology, China
Tue, 5 Aug, 11:30 - 11:45

TU2.M3.5: HOW CAN MULTIMODAL REMOTE SENSING DATASETS TRANSFORM CLASSIFICATION VIA SPATIALNET-VIT?
Gautam Siddharth Kashyap, Macquarie University, Australia; Manaswi Kulahara, TERI School Of Advanced Studies, India; Nipun Joshi, Cornell University, United States; Usman Naseem, Macquarie University, Australia