Yasuhiro Oikawa
Papers
3
Total Citations
23
H-Index
2
About
Yasuhiro Oikawa is a researcher working at the intersection of audio signal processing, computer vision, and robotics, with a particular focus on acoustic sensing and spatial sound analysis. His most recognized contribution lies in the development of self-supervised neural approaches to audio-visual sound source localization, a challenging problem that addresses how autonomous systems can identify and locate sounding objects within their visual field without relying on exhaustive manual labeling. By employing probabilistic spatial modeling, Oikawa's work offers a scalable solution to a problem that would otherwise be impractical due to the enormous variety of sounding objects in real-world environments — a paper that has garnered 16 citations since its 2020 publication. Beyond audio-visual learning, Oikawa has demonstrated a keen interest in environmental noise mapping, contributing research on three-dimensional acoustic measurement systems utilizing unmanned aerial vehicles, specifically aerial blimp robots, to efficiently construct detailed noise maps at reduced cost. This work reflects his broader commitment to developing intelligent, practical systems that enhance robotic perception and environmental monitoring, making his research highly relevant to both academic robotics communities and real-world autonomous applications.
Research Focus
Key Achievements
Top Papers
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