This inventor holds 4 USPTO granted patents and 4 published patent applications. Top assignees: Wisconsin Alumni Research Foundation, Cornell University, Purdue Research Foundation. Active years: 2024-2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:



Years Active: 2024-2026
Title: Innovations by Inventor Yin Li
Introduction
Yin Li is an accomplished inventor based in Madison, WI (US). He has made significant contributions to the field of technology, particularly in machine learning and hand pose tracking. With a total of 4 patents, his work showcases innovative approaches to complex problems.
Latest Patents
Yin Li's latest patents include "Vision transformers leveraging temporal redundancy" and "Deep continuous 3D hand pose tracking." The first patent discloses methods and systems for processing frame data, which involve obtaining a sequence of data and applying it to a machine learning model. This model is designed to determine token-level errors and produce machine learning output scores based on buffer representations. The second patent describes a wrist-mounted system for tracking hand poses, utilizing low-profile cameras mounted on a wearable band. This system captures images of the back of the hand to infer hand poses and gestures, demonstrating a practical application of imaging technology.
Career Highlights
Yin Li has worked with notable organizations such as the Wisconsin Alumni Research Foundation and Cornell University. His experience in these institutions has allowed him to develop and refine his innovative ideas, contributing to advancements in his field.
Collaborations
Yin Li has collaborated with Fang Hu, who is a talented woman in the field. Their partnership has likely fostered a creative environment for developing new technologies and solutions.
Conclusion
Yin Li's contributions to technology through his patents and collaborations highlight his innovative spirit and dedication to advancing machine learning and hand tracking systems. His work continues to influence the industry and inspire future innovations.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile