Kentaro Yanagihara

University of Fukui, Oki Electric Industry (Japan)

Papers

Total Citations

H-Index

About

Kentaro Yanagihara is a researcher whose work bridges the critical intersection of computer vision and reliable wireless communications. His most impactful contribution addresses the notoriously difficult problem of **cross-season place recognition** for autonomous systems. In his 2015 paper, Yanagihara proposed a novel approach that leverages **image-based priors** to create compact, discriminative scene descriptors. This method enables a robot or vehicle to recognize a location even when its appearance has been dramatically altered by seasonal changes—such as snow covering summer foliage—achieving robust performance where traditional methods fail. With **21 citations**, this work has become a foundational reference for researchers tackling long-term visual localization. Earlier in his career, Yanagihara also made notable contributions to **wireless multi-hop networks**. His 2012 paper introduced a **distant multipath routing method** that enhances data transmission reliability by redundantly sending packets through multiple, spatially diverse routes. This technique effectively leverages route diversity to mitigate packet loss, offering a practical solution for robust communication in challenging environments. Yanagihara’s work demonstrates a unique ability to solve real-world reliability problems, whether for a robot navigating a changing landscape or data traversing a fragile network.