Kai Zeng

USPTO Granted Patents = 11 (Patent Applications = 2)

EPO Patents = 3 (Patent Applications = 11)

Average Co-Inventor Count = 3.9

ph-index = 2

Forward Citations = 10(Granted Patents)

Location History:

North York, CA (2018)
Kitchener, CA (2020 - 2024)

Company Filing History:

Years Active: 2018-2025

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11 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12463757 - Automatic visual media transmission error assessment (2025-11-04),

2. 12333741 - No-reference visual media assessment combining deep neural networks and models of human visual system and video content/distortion analysis (2025-06-17),

3. 12262097 - Unified end-to-end quality and latency measurement, optimization and management in multimedia communications (2025-03-25),

4. 11962781 - Video encoding complexity measure system (2024-04-16),

5. 11856204 - Macroblocking artifact detection (2023-12-26),

6. 11638051 - Real-time latency measurement of video streams (2023-04-25),

7. 11616959 - Relationship modeling of encode quality and encode parameters based on source attributes (2023-03-28),

8. 11477351 - Image and video banding assessment (2022-10-18),

9. 11363345 - Unified end-to-end quality and latency measurement, optimization and management in multimedia communications (2022-06-14),

10. 10863217 - Method and system for smart adaptive video streaming driven by perceptual quality-of-experience estimations (2020-12-08),

11. 10165281 - Method and system for objective perceptual video quality assessment (2018-12-25),

Title: Innovations of Inventor Kai Zeng

Introduction

Kai Zeng is a notable inventor based in Kitchener, Canada. He has made significant contributions to the field of visual media transmission, holding a total of 11 patents. His work focuses on improving the quality and reliability of visual media communication systems.

Latest Patents

Among his latest patents is a method for automatic visual media transmission error assessment. This innovative system assesses transmission errors in visual media inputs by utilizing content analysis, codec analysis, distortion analysis, and human visual system modeling. The visual media input is divided into partitions, which are processed through deep neural networks (DNNs). The outputs from these partitions are combined with domain knowledge to produce a comprehensive assessment of transmission errors. Additionally, he has developed a no-reference visual media assessment method that combines deep neural networks with models of the human visual system and video content distortion analysis. This method decomposes test visual media inputs into multiple-channel representations, producing an overall quality score based on DNN outputs.

Career Highlights

Kai Zeng has worked with several prominent companies, including Ssimwave Inc. and Imax Corporation. His experience in these organizations has allowed him to refine his expertise in visual media technologies and contribute to groundbreaking innovations.

Collaborations

Throughout his career, Zeng has collaborated with notable individuals in the field, including Zhou Wang and Hojatollah Yeganeh. These partnerships have further enhanced his research and development efforts.

Conclusion

Kai Zeng's contributions to visual media technology through his patents and collaborations highlight his role as an influential inventor in the industry. His innovative approaches continue to shape the future of visual media communication systems.

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