摘要
由一名新闻记者兼机器人与机器学习的新闻编辑每日新闻-调查人员发布了关于马学习的新报告。根据News Rx记者从英国伦敦发来的新闻报道，研究表明，“即将在月球和其他行星物体上进行的机器人和人类活动将受益于先进的原位计算机探测和机器学习能力，以识别和量化微粒地球污染物、月球表土扰动、行星际尘埃的通量、可能的星际尘埃、FL流星体，Yolo-ET(ExtraTerrestrial)算法是该领域的一项创新，它专门针对这些挑战进行了微调。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting from London, United Kingdom, by News Rx journalists, research stated, “Imminent robotic and human activities on the M oon and other planetary bodies would benefit from advanced in situ Computer Visi on and Machine Learning capabilities to identify and quantify microparticle terr estrial contaminants, lunar regolith disturbances, the flux of interplanetary du st particles, possible interstellar dust, fl -meteoroids, and secondary impact e jecta. The YOLO-ET (ExtraTerrestrial) algorithm, an innovation in this field, fi ne-tunes Tiny-YOLO to specifically address these challenges.”
NETL
NSTL