Fangzhe Chang

Title: Fangzhe Chang: Innovator in Deep Neural Networks and Video Comparison Technologies

Introduction

Fangzhe Chang is a prominent inventor based in Edison, NJ (US), known for his contributions to the fields of deep neural networks and video processing. With a total of 6 patents to his name, he has made significant strides in enhancing the efficiency and effectiveness of machine learning technologies.

Latest Patents

Chang's latest patents include groundbreaking systems and methods for training neural networks. One notable invention is a system designed for coordinated heterogeneous processing of training data for deep neural networks. This system features a memory that stores samples of training data and a distributor that identifies multiple work servers for processing these samples. The distributor assesses the Graphics Processing Unit (GPU) processing powers of the servers, determines differences in their capabilities, and allocates training samples accordingly. Another significant patent involves a method and apparatus for comparing videos. This method partitions frames from both query and target videos into blocks, calculates mean intensity values, and produces time series that help determine alignment between the two videos.

Career Highlights

Throughout his career, Fangzhe Chang has worked with notable companies such as Alcatel Lucent and Alcatel-Lucent USA Inc. His experience in these organizations has contributed to his expertise in developing innovative technologies that address complex challenges in data processing and analysis.

Collaborations

Chang has collaborated with esteemed colleagues, including Thomas L. Wood and Yansong Ren, who have contributed to his research and development efforts in the field.

Conclusion

Fangzhe Chang's innovative work in deep neural networks and video comparison technologies showcases his significant impact on the industry. His patents reflect a commitment to advancing machine learning and data processing methodologies.