Evaluation of Resource-Efficient Crater Detectors on Embedded Systems
<|reference_start|>Evaluation of Resource-Efficient Crater Detectors on Embedded Systems: 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.<|reference_end|>
@article{vellas2024evaluation,
    title={Evaluation of Resource-Efficient Crater Detectors on Embedded Systems},
    author={Simon Vellas, Bill Psomas, Kalliopi Karadima, Dimitrios Danopoulos,
  Alexandros Paterakis, George Lentaris, Dimitrios Soudris, Konstantinos
  Karantzalos},
    journal={arXiv preprint arXiv:2405.16953},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.16953},
    primaryClass={cs.CV cs.DC cs.PF}
}