Company Filing History:
Years Active: 2020-2022
Title: Innovations by Shukai Chen in Face and Finger Vein Recognition
Introduction
Shukai Chen is a prominent inventor based in Beijing, China. He has made significant contributions to the fields of face recognition and biometric identification technologies. With a total of three patents to his name, Chen's work focuses on enhancing the accuracy and efficiency of identification systems.
Latest Patents
One of Chen's latest patents is a "Method and system for face recognition via deep learning." This innovative method utilizes deep learning techniques to improve face identification. The process involves acquiring an aligned face image, scaling it to a target image, and extracting a pixel matrix for input into a neural network model. The multilayer computing executed by the model yields a computing result, which is then compared to a facial template vector using cosine similarity. This method significantly enhances both the identification success rate and speed.
Another notable patent is the "Finger vein identification method and device." This invention effectively extracts finger vein characteristics for identification purposes. The method includes collecting a finger vein image, employing line fitting to identify regions of interest, and conducting geometric and grayscale normalization. The resulting finger vein blood vessel image is then used for identification, showcasing Chen's expertise in biometric technologies.
Career Highlights
Shukai Chen has worked with notable companies such as ZKTeco Co., Ltd. and ZKTeco USA LLC. His experience in these organizations has allowed him to develop and refine his innovative ideas in biometric identification systems.
Collaborations
Chen has collaborated with talented individuals in his field, including Quanhong Che and Feiyang Tong. These partnerships have contributed to the advancement of his research and the successful development of his patented technologies.
Conclusion
Shukai Chen's contributions to face and finger vein recognition technologies demonstrate his commitment to innovation in biometric identification. His patents reflect a deep understanding of deep learning and identification methods, positioning him as a key figure in this evolving field.