FR1.B3.4
The Cubesat Case Study: Resource- Efficient Deep Learning For Space Application
Surendra Bohara, Alison Shilpakar, Kushal KC, Sujan Tyata, Abhas Maskey, Antarikchya Pratisthan Nepal, Nepal
Session:
FR1.B3: Al for On-board Satellite Analytics Oral
Track:
Special Scientific Themes
Location:
Room B3
Presentation Time:
Friday, 8 August, 08:45 - 09:00
Presentation
Discussion
Resources
No resources available.
Session FR1.B3
FR1.B3.1: MULTIMODAL REGISTRATION VIA REUSABLE ENCODERS FOR ONBOARD CHANGE DETECTION
Monikka Roslianna Busto, Takeharu Eda, Hiroyuki Makino, Nippon Telegraph and Telephone Corporation, Japan
FR1.B3.2: TRANSFORMING VOLCANIC MONITORING: A DATASET AND BENCHMARK FOR ONBOARD VOLCANO ACTIVITY DETECTION
Darshana Priyasad, Tharindu Fernando, Maryam Haghighat, Harshala Gammulle, Clinton Fookes, Queensland University of Technology, Australia
FR1.B3.3: Partial Least Squares Regression Chlorophyll-a Estimation Pipeline for HYPSO-1 & -2 Hyperspectral Cube Satellites
Cameron Penne, Perumthuruthil Suseelan Vishnu, Milica Orlandić, Norwegian University of Science and Technology, Norway
FR1.B3.4: The Cubesat Case Study: Resource- Efficient Deep Learning For Space Application
Surendra Bohara, Alison Shilpakar, Kushal KC, Sujan Tyata, Abhas Maskey, Antarikchya Pratisthan Nepal, Nepal
FR1.B3.5: Optimized AI Model Development for On-Board Image Classification in CubeSats using BIRDS Satellite Imagery
Dexter James Cuaresma, Adamson University, Philippines; Dylan Josh Lopez, De La Salle University, Philippines; Mark Angelo Purio, Adamson University, Philippines
Resources
No resources available.