Shuhui Qu

Title: Shuhui Qu: Innovator in Video and Image Processing Technologies

Introduction

Shuhui Qu is a prominent inventor based in Fremont, CA, known for his contributions to video and image processing technologies. With a total of 11 patents, Qu has made significant advancements in the field, particularly in the areas of anomaly detection and defect detection in manufacturing displays.

Latest Patents

Qu's latest patents include innovative systems designed for enhancing image and video processing. One notable patent is for a "Vector quantized auto-encoder codebook learning for manufacturing display extreme minor defects detection." This system comprises a memory, an encoder, a decoder, and a processor. The processor is connected to the memory, encoder, and decoder, and is configured to receive an input image, divide it into multiple image patches, and select corresponding codes from a codebook. The system further determines an assigned code matrix and generates a reconstructed image based on this matrix.

Another significant patent is the "Method for video-based patch-wise vector quantized auto-encoder codebook learning for video anomaly detection." This system operates similarly, receiving an input video, dividing it into video patches, and selecting codes from a codebook. It also determines an assigned code matrix and generates a reconstructed video based on this matrix.

Career Highlights

Throughout his career, Shuhui Qu has worked with leading companies in the technology sector, including Samsung Display Co., Ltd. and Samsung Electronics Co., Ltd. His experience in these organizations has contributed to his expertise in developing advanced processing systems.

Collaborations

Qu has collaborated with notable colleagues, including Janghwan Lee and Sai MarapaReddy, who have contributed to his projects and innovations in the field.

Conclusion

Shuhui Qu's work in video and image processing technologies showcases his innovative spirit and dedication to advancing the field. His patents reflect a commitment to improving manufacturing processes and enhancing video anomaly detection systems.