This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Huawei Technologies Co., Ltd.. Active years: 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: 2026
Title: Hengtong Hu: Innovator in Semi-Supervised Learning
Introduction
Hengtong Hu is a prominent inventor based in Shenzhen, China. He has made significant contributions to the field of artificial intelligence, particularly in the area of semi-supervised learning models. His innovative approach has the potential to enhance computer vision applications.
Latest Patents
Hengtong Hu holds a patent for a "Training method for semi-supervised learning model, image processing method, and device." This patent describes a method that predicts classification categories of unlabeled samples using a trained semi-supervised learning model. The process involves determining the accuracy of prediction labels in a one-bit labeling manner, which simplifies the annotation process. By reconstructing the training set based on this information, the model's prediction accuracy can be significantly improved.
Career Highlights
Hengtong Hu is currently employed at Huawei Technologies Co., Ltd., where he continues to develop cutting-edge technologies in artificial intelligence. His work focuses on enhancing machine learning techniques and improving the efficiency of image processing methods.
Collaborations
Hengtong has collaborated with notable colleagues such as Zewei Du and Lingxi Xie, contributing to various projects that advance the field of artificial intelligence.
Conclusion
Hengtong Hu's innovative work in semi-supervised learning exemplifies the potential of artificial intelligence in transforming computer vision applications. His contributions are paving the way for future advancements in this exciting field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile