Cheng Chang

Title: Innovations by Inventor Cheng Chang

Introduction

Cheng Chang, an innovative inventor based in Toronto, Canada, has made remarkable contributions to the fields of image processing and retrieval. With a total of 5 patents to his name, Cheng has developed advanced systems that leverage deep learning and graph-based technologies to enhance image identification and processing.

Latest Patents

Among Cheng's latest patents is the "Automated Image Retrieval with Image Graph." This innovative image retrieval system receives an image to identify relevant images from an extensive image repository. In this system, images are represented in an image retrieval graph, where nodes are interconnected by edges indicating the similarity of images. The system utilizes a two-step process of exploration and traversal to identify and retrieve relevant images based on the received input.

Another notable patent is the "System and Method for Image Processing Using Deep Neural Networks." This invention implements deep learning techniques on mobile devices to provide real-time video processing using a convolutional neural network (CNN). The system efficiently processes images to create accurate hair mattes, allowing for color and texture adjustments. By combining features from various neural network layers, the CNN can achieve high-resolution output while maintaining effective color adjustments.

Career Highlights

Cheng Chang has had a dynamic career, including significant roles at renowned companies such as the Toronto-Dominion Bank and L'Oréal. His experience in these industries has greatly influenced his innovative capacity and the development of his patents.

Collaborations

Throughout his career, Cheng has collaborated with talented individuals, including Maksims Volkovs and Guangwei Yu. These partnerships have fostered an environment of creativity and innovation, enhancing the effectiveness of his projects and patents.

Conclusion

Cheng Chang stands out as a forward-thinking inventor whose work in automated image retrieval and deep learning image processing demonstrates the power of innovation in technology. With his continued contributions, he is likely to inspire future advancements in the field and beyond.