TH4.M1.2
A Hybrid Deep Learning and Object-Based Image Analysis Framework for Enhanced Landslide Detection
Amit Kumar Singh, Sapienza University of Rome, Italy; Kanishka Pujara, Indian Institute of Technology Roorkee, India; Giovanni Pugliano, Oscar Rosario Belfiore, Guido D’Urso, University of Naples Federico II, Italy
Session:
TH4.M1: Satellite-Based Remote Sensing for Disaster Response I Oral
Track:
Community-Contributed Sessions
Location:
Room M1
Presentation Time:
Thursday, 7 August, 16:00 - 16:15
Presentation
Discussion
Resources
No resources available.
Session TH4.M1
TH4.M1.1: Analysis of infrared brightness temperature and potential coupling responses of partly loaded rock specimen during pre-peak and post-peak loading process
Licheng Sun, Lixin Wu, Youyou Xu, Tao Zheng, Guangrui Dong, Wenfei Mao, Central South University, China
TH4.M1.2: A Hybrid Deep Learning and Object-Based Image Analysis Framework for Enhanced Landslide Detection
Amit Kumar Singh, Sapienza University of Rome, Italy; Kanishka Pujara, Indian Institute of Technology Roorkee, India; Giovanni Pugliano, Oscar Rosario Belfiore, Guido D’Urso, University of Naples Federico II, Italy
TH4.M1.3: Remote Sensing for Humanitarian Assistance and Disaster Relief
Joshua Broadwater, Beatrice Garcia, Johns Hopkins University, United States
TH4.M1.4: TOWARDS FREQUENT FLOOD INUNDATION MONITORING USING AI AND EO
Antara Dasgupta, Paul Hosch, RWTH Aachen University, Germany; Rakesh Sahu, Galgotias University, India; Björn Waske, Universität Osnabrück, Germany
TH4.M1.5: STUDY ON THE EVALUATION OF OPTIMAL REMOTE SENSING FEATURES FOR BUSHFIRE
Ziyi Yang, Husam Al-Najjar, University of Technology Sydney, Australia; Bahareh Kalantar, RIKEN Center for Advanced Intelligence Project, Disaster, Japan; Ghassan Beydoun, University of Technology Sydney, Australia
Resources
No resources available.