تقرير
Evaluation of Resource-Efficient Crater Detectors on Embedded Systems
العنوان: | Evaluation of Resource-Efficient Crater Detectors on Embedded Systems |
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المؤلفون: | Vellas, Simon, Psomas, Bill, Karadima, Kalliopi, Danopoulos, Dimitrios, Paterakis, Alexandros, Lentaris, George, Soudris, Dimitrios, Karantzalos, Konstantinos |
سنة النشر: | 2024 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Performance |
الوصف: | Real-time analysis of Martian craters is crucial for mission-critical operations, including safe landings and geological exploration. This work leverages the latest breakthroughs for on-the-edge crater detection aboard spacecraft. We rigorously benchmark several YOLO networks using a Mars craters dataset, analyzing their performance on embedded systems with a focus on optimization for low-power devices. We optimize this process for a new wave of cost-effective, commercial-off-the-shelf-based smaller satellites. Implementations on diverse platforms, including Google Coral Edge TPU, AMD Versal SoC VCK190, Nvidia Jetson Nano and Jetson AGX Orin, undergo a detailed trade-off analysis. Our findings identify optimal network-device pairings, enhancing the feasibility of crater detection on resource-constrained hardware and setting a new precedent for efficient and resilient extraterrestrial imaging. Code at: https://github.com/billpsomas/mars_crater_detection. Comment: Accepted at 2024 IEEE International Geoscience and Remote Sensing Symposium |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2405.16953 |
رقم الأكسشن: | edsarx.2405.16953 |
قاعدة البيانات: | arXiv |
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