Company Filing History:
Years Active: 2022
Title: Innovations of Pingping Zhang in Image Segmentation
Introduction
Pingping Zhang is a notable inventor based in Dalian, China. He has made significant contributions to the field of image processing, particularly through his innovative patent related to convolutional neural networks (CNNs). His work focuses on enhancing image segmentation techniques, which are crucial in various applications, including computer vision and artificial intelligence.
Latest Patents
Pingping Zhang holds a patent for a "Method for image segmentation using CNN." This invention utilizes an encoder-decoder structure within a convolutional neural network to improve segmentation accuracy. The method incorporates a multi-scale context aggregation module that processes encoded feature maps, aggregating information from global to local scales. This approach strengthens the semantic relationships of different scales, ultimately enhancing the precision of image segmentation. To optimize computational efficiency, a channel-wise feature selection module is employed in the decoder, ensuring that only the most relevant features are preserved and enhanced.
Career Highlights
Pingping Zhang is affiliated with the Hong Kong Applied Science and Technology Research Institute Company Limited. His work at this institution has allowed him to explore advanced methodologies in image processing and contribute to the development of cutting-edge technologies. His innovative approach has garnered attention in the research community, showcasing his expertise in the field.
Collaborations
Pingping Zhang has collaborated with several talented individuals, including Shangping Liu and Lu Wang. These collaborations have fostered a productive environment for research and innovation, leading to advancements in their respective fields.
Conclusion
Pingping Zhang's contributions to image segmentation through his patented methods highlight his role as a leading inventor in the field of artificial intelligence. His innovative techniques continue to influence advancements in image processing technologies.