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Years Active: 2013-2026
Title: The Innovative Mind of Yusuke Shinohara
Introduction
Yusuke Shinohara, based in Tokyo, Japan, is a prolific inventor with a remarkable portfolio of 13 patents to his name. His work primarily focuses on visual object tracking and machine learning, showcasing his deep understanding of technology and innovation.
Latest Patents
Among his latest contributions to the field are patents related to a visual object tracking method and system, as well as machine learning methods and learning systems. One of his innovative patents involves an estimation unit within a visual object tracking apparatus that estimates multiple estimated bounding boxes and corresponding object IDs. This technology operates by analyzing detected bounding boxes from moving images to predict future object positions. Additionally, his learning apparatus patent encompasses a sophisticated model that utilizes a combination of features to accurately label input sequences, demonstrating his advanced approach to machine learning.
Career Highlights
Shinohara's impressive career includes significant roles at renowned companies such as NEC Corporation and Nippon Telegraph and Telephone Corporation. His contributions to these organizations have been pivotal in advancing technological solutions, particularly in the realm of visual recognition and automated learning systems.
Collaborations
Throughout his career, Yusuke Shinohara has collaborated with esteemed colleagues like Yasunobu Chiba and Hayato Itsumi. These partnerships have fostered innovation and enabled the development of groundbreaking technologies that enhance visual tracking and data learning methodologies.
Conclusion
Yusuke Shinohara stands out as an influential inventor in the technology sector, with a strong focus on visual object tracking and machine learning. His numerous patents reflect his dedication to innovation and his ongoing impact on the field. As technological advancements continue to grow, Shinohara's work will undoubtedly play a critical role in shaping the future of object recognition and automation.