This inventor holds 2 USPTO granted patents. Top assignee: The University of Texas System. Active years: 2022-2023.
Location History:
- Austin, TX (US) (2022)
- Boston, MA (US) (2023)
Company Filing History:
Years Active: 2022-2023
Title: Suyog Dutt Jain: Innovator in Image and Video Segmentation
Introduction
Suyog Dutt Jain is a prominent inventor based in Austin, TX (US). He has made significant contributions to the field of image and video processing, particularly in the segmentation of generic foreground objects. With a total of 2 patents to his name, Jain's work is at the forefront of technological advancements in computer vision.
Latest Patents
Jain's latest patents focus on a method, system, and computer program product for segmenting generic foreground objects in images and videos. The process involves using a first deep neural network to process an appearance stream of an image in a video frame. Additionally, a second deep neural network processes a motion stream of an optical flow image in the same video frame. By combining the appearance and motion streams, Jain's method effectively performs segmentation of generic objects in the video frame. Furthermore, his approach to segmenting generic foreground objects in images involves training a convolutional deep neural network to estimate the likelihood that a pixel belongs to a foreground object, thereby enhancing the accuracy of image analysis.
Career Highlights
Suyog Dutt Jain is affiliated with the University of Texas System, where he continues to innovate and contribute to research in his field. His work has garnered attention for its practical applications in various industries, including entertainment and security.
Collaborations
Jain has collaborated with notable colleagues such as Kristen Grauman and Bo Xiong, further enriching his research and development efforts.
Conclusion
Suyog Dutt Jain is a key figure in the realm of image and video segmentation, with innovative patents that push the boundaries of technology. His contributions are vital for advancements in computer vision and related fields.