摘要
由一名新闻记者-机器人与机器学习每日新闻编辑-研究人员详细介绍了机器人S-机器人和自动化的新数据。根据来自中国沈阳的新闻，由NewsRx的记者报道，研究表明：“字母introduced了一种新的视觉位置识别(VPR)方法，称为轻量级池中心视觉感知VPR(LPS-VPR)，该方法的关键贡献是基于池的显著性编码器(PSE)，它能有效地将局部上下文显著性线索嵌入图像中，并利用诸如注意力提取显著性线索等计算密集型操作进行识别。本研究经费来源于国家重点研究开发项目。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Robotic s - Robotics and Automation. According to news originating from Shenyang, People ’s Republic of China, by NewsRx correspondents, research stated, “The letter int roduces a novel Visual Place Recognition (VPR) method called Lightweight Pooling -centric Saliency-aware VPR (LPS-VPR), a high-performance VPR method capable of exploiting saliency information without computational burden. The key contributi on of the method is a pooling-based saliency encoder (PSE) that efficiently extr acts and integrates local context saliency cues into the image embedding, avoidi ng using computationally intensive operations such as attention for saliency cue s extraction.” Financial support for this research came from National Key Research and Developm ent Program of China.
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