Tokyo, Japan

Takahito Kawanishi

This inventor holds 20 USPTO granted patents and 4 published patent applications and 2 EPO patents, primarily in Image Processing Technology. Top assignees: Nippon Telegraph and Telephone Corporation, Massachusetts Institute of Technology, The University of Tokyo. Active years: 2018-2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Takahito Kawanishi. Retrieved from https://idiyas.com/inventor/takahito-kawanishi

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 20 

% Patents Active = 100.0

 

Average Co-Inventor Count = 4.2

ph-index = 2

Forward Citations = 7(Granted Patents)


Location History:

  • Atsugi, JP (2018 - 2022)
  • Tokyo, JP (2021 - 2024)
  • Musashino, JP (2023 - 2024)

Company Filing History:


Years Active: 2018-2025

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Areas of Expertise:
Depth Estimation
Image Adjustment
Illegal Content Detection
Learning Device
Commercial Information
Signal Encoding
Retrieval Method
Content Determination
Sponsorship Credit
Training Apparatus
Similarity Matrix
20 patents (USPTO):Explore Patents

Title: The Innovative Mind of Takahito Kawanishi

Introduction

Takahito Kawanishi is a prominent inventor based in Tokyo, Japan. With a remarkable portfolio boasting 18 patents, he has made significant contributions to the fields of depth estimation and image processing. His inventions showcase a blend of creativity and technical expertise, pushing the boundaries of what's possible in technology.

Latest Patents

Among his latest patents, Kawanishi has developed several cutting-edge technologies, particularly focused on depth estimation and image adjustment. His patents include:

1. **Depth estimation device**: This device employs an acquiring unit that captures input images, which are then processed to generate a detailed depth map that provides depth information for each pixel of the image.

2. **Depth estimation model learning device**: This device utilizes a depth estimator model to minimize errors in depth estimation by adjusting loss function values based on pixel error thresholds.

3. **Depth estimation method**: This involves a systematic approach to deriving depth maps from input images, ensuring accurate representation of spatial depth.

4. **Depth estimation model learning method**: This method refines how depth models are learned, focusing on optimizing the prediction accuracy for various depth scenarios.

5. **Depth estimation program**: A program that integrates these components to provide a cohesive solution for depth estimation, significantly enhancing image processing capabilities.

Additionally, Kawanishi has invented an image adjustment apparatus that includes multiple components to isolate and modify grayscale images and enhance their visual contrast. This sophisticated device not only derives illumination and reflectance components but also creates conversion functions to align histograms, thereby improving image quality.

Career Highlights

Kawanishi has had a distinguished career in research and development. He has worked with notable organizations, including Nippon Telegraph and Telephone Corporation as well as The University of Tokyo. His tenure in these esteemed institutions has significantly influenced his pioneering work in imaging technologies and depth estimation models.

Collaborations

Throughout his career, Kawanishi has collaborated with esteemed colleagues, including Kunio Kashino and Yasunori Oishi. These partnerships have fostered a creative environment that enables innovative problem-solving and the development of advanced technologies.

Conclusion

Takahito Kawanishi’s contributions to innovation, especially in depth estimation and image processing, highlight the importance of creativity and technical prowess in advancing modern technology. His body of work serves as an inspiration to current and future inventors, showcasing the impact that a dedicated inventor can have on our understanding of visual data processing.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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