Company Filing History:
Years Active: 2020-2022
Title: Innovations of Lin Wang in Real-Time Detection and 3D Printing Technologies
Introduction
Lin Wang is an accomplished inventor based in Wuxi, China. He has made significant contributions to the fields of deep learning and 3D printing technologies. With a total of 2 patents, his work focuses on enhancing real-time object detection and improving food material preparation for 3D printing.
Latest Patents
One of Lin Wang's latest patents is a real-time target detection method deployed on a platform with limited computing resources. This invention improves the YOLO-v3-tiny neural network by introducing a modified version called Tinier-YOLO. The model size of Tinier-YOLO is only 7.9 MB, significantly smaller than its predecessors, while maintaining real-time performance and accuracy. The real-time performance of Tinier-YOLO is 21.8% higher than that of YOLO-v3-tiny and 70.8% higher than YOLO-v2-tiny. Additionally, the accuracy of Tinier-YOLO is increased by 10.1% compared to YOLO-v3-tiny and nearly 18.2% compared to YOLO-v2-tiny.
Another notable patent is a control method for improving the forming and 3D precise printing performance of a thawed surimi system. This invention relates to the preparation technologies of food materials for 3D printing. The method involves several steps, including thawing, mixing, grinding, printing, and cooking. The resulting surimi gel system allows for reduced printing temperatures and increased discharging rates, enabling the creation of fish products that retain their original properties and taste.
Career Highlights
Lin Wang is affiliated with Jiangnan University, where he continues to innovate and contribute to research in his fields of expertise. His work has garnered attention for its practical applications and advancements in technology.
Collaborations
Lin Wang collaborates with notable colleagues, including Min Zhang and Dongcui Fan, who contribute to his research endeavors.
Conclusion
Lin Wang's innovative patents in real-time detection and 3D printing technologies showcase his commitment to advancing these fields. His contributions not only enhance existing technologies but also pave the way for future developments in deep learning and food material preparation.