Anyang-si, South Korea

Yong-Hwan Kim

USPTO Granted Patents = 6 

Average Co-Inventor Count = 4.9

ph-index = 2

Forward Citations = 41(Granted Patents)


Location History:

  • Anyang, KR (2008)
  • Kyunggi-do, KR (2012)
  • Anyang-si, KR (2010 - 2020)

Company Filing History:


Years Active: 2008-2020

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6 patents (USPTO):Explore Patents

Title: Yong-Hwan Kim: Innovator in Multi-View Video Codec Technology

Introduction

Yong-Hwan Kim is a prominent inventor based in Anyang-si, South Korea. He has made significant contributions to the field of video coding technology, holding a total of 6 patents. His work focuses on improving coding efficiency in multi-view video codecs, which is crucial for enhancing video quality and compression.

Latest Patents

One of Yong-Hwan Kim's latest patents is a method for image prediction of a multi-view video codec and a computer-readable recording medium therefor. This innovative method involves partitioning an image into multiple base blocks and acquiring information from reference images that are temporally different and have different views. By predicting a target block based on this acquired information, the method generates an image that closely resembles the view currently being compressed. This approach significantly improves coding efficiency by utilizing multiple images from different perspectives.

Career Highlights

Yong-Hwan Kim is affiliated with the Korea Electronics Technology Institute, where he continues to advance research in video coding technologies. His expertise and innovative methods have positioned him as a key figure in the development of efficient video compression techniques.

Collaborations

Yong-Hwan Kim has collaborated with notable colleagues, including Je-Woo Kim and Ji-Ho Park. Their combined efforts contribute to the ongoing advancements in the field of electronics and video technology.

Conclusion

Yong-Hwan Kim's contributions to multi-view video codec technology exemplify his commitment to innovation and efficiency in video processing. His patents reflect a deep understanding of the complexities involved in image prediction and coding, making him a valuable asset to the field.

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