Company Filing History:
Years Active: 2025
Title: Innovations of Huiwen Chang
Introduction
Huiwen Chang is a notable inventor based in Cambridge, MA (US). He has made significant contributions to the field of technology, particularly in image processing and watermark extraction. With a total of six patents to his name, Chang continues to push the boundaries of innovation.
Latest Patents
One of his latest patents is titled "Flexible image aspect ratio using machine learning." This invention allows a computing device to adjust the aspect ratio of an image to match that of a display area. The device receives an image with a first aspect ratio and obtains a second aspect ratio for the display area. It then extends the image to include additional features and automatically crops it around an identified region of interest. This ensures that the cropped image fits perfectly within the display area.
Another significant patent is "Zoom agnostic watermark extraction." This invention involves methods and systems for determining a watermark's visibility in an image. A watermark decoder applies a machine learning model to decode watermarks at various zoom levels. The decoder outputs results based on whether a watermark was successfully decoded, providing valuable insights into watermark extraction technology.
Career Highlights
Huiwen Chang is currently employed at Google Inc., where he continues to innovate and develop new technologies. His work has garnered attention in the tech community, and his patents reflect his expertise in machine learning and image processing.
Collaborations
Chang collaborates with talented individuals in his field, including Feng Yang and Xiyang Luo. Their combined efforts contribute to the advancement of technology and innovation at Google Inc.
Conclusion
Huiwen Chang is a prominent inventor whose work in image processing and watermark extraction has made a significant impact in the tech industry. His innovative patents demonstrate his commitment to advancing technology and improving user experiences.