Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration

ArXi:2508.18025v4 Announce Type: replace Autonomous planetary exploration demands real-time, high-fidelity environmental perception. Standard deep learning models require massive computational resources. Conversely, space-qualified onboard computers operate under strict power, thermal, and memory limits. This disparity creates a severe engineering bottleneck, preventing the deployment of highly capable perception architectures on extraterrestrial exploration platforms.