For the Inventor, By the Inventor

Enter assignee name

Kansas City, MO, United States of America

Dst Technologies, Inc.

Calculating rank

USPTO Granted Patents = 28

% Expired Patents = 14.3

CIPO Patents = 1

Trademarks = 3

Forward Citations = 76

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25 inventors (with patents filed for the assignee):

Paul Martin Ives (10 out of 10 patents)

Peter E Clark (8 out of 8 patents)

Michael V Gentry (8 out of 8 patents)

4. Hui Peng Hu (7 out of 14 patents)

5. Ramesh Sridharan (5 out of 7 patents)

6. Deni Esposito (5 out of 5 patents)

7. Kevin W Stokes (3 out of 3 patents)

8. Chin Hsu (3 out of 3 patents)

9. Huguens Jean (2 out of 4 patents)

10. Yoriyasu Yano (2 out of 5 patents)

11. Kuang Chen (2 out of 5 patents)

12. Joshua O Highley (2 out of 2 patents)

13. Ehsan Hosseini Asl (1 out of 2 patents)

14. Michail Iliadis (1 out of 2 patents)

15. Keith Bessinger (1 out of 1 patent)

Core Competencies:

Scalable Form Matching

Image Feature Identification

Few-Shot Learning

Data Extraction

Digital Image Analysis

Handwritten Information Segregation

Document Fingerprinting

Contextualization

Candidate Identification

Print Shift Compensation

Machine Indeterminable Information

Virtual Communication Service

28 patents: Sort by Forward Citations

1. 12561519 - Scalable form matching (2026-02-24),

2. 11868394 - Analyzing content of digital images (2024-01-09),

3. 11861471 - Computer vision image feature identification via multi-label few-shot model (2024-01-02),

4. 11847418 - Few-shot language model training and implementation (2023-12-19),

5. 11610418 - Identifying versions of a form (2023-03-21),

6. 11508172 - Identifying location of shreds on an imaged form (2022-11-22),

7. 11308319 - Computer vision image feature identification via multi-label few-shot model (2022-04-19),

8. 11238275 - Computer vision image feature identification via multi-label few-shot model (2022-02-01),

9. 11182640 - Analyzing content of digital images (2021-11-23),

10. 11062092 - Few-shot language model training and implementation (2021-07-13),

11. 10963685 - Generating variations of a known shred (2021-03-30),

12. 9411547 - Compensation for print shift in standardized forms to facilitate extraction of data therefrom (2016-08-09),

13. 9336437 - Segregation of handwritten information from typographic information on a document (2016-05-10),

14. 9262679 - System and method for identification and separation of form and feature elements from handwritten and other user supplied elements (2016-02-16),

15. 9240999 - Managed virtual point to point communication service having verified directory, secure transmission and controlled delivery (2016-01-19),

Company Overview

Dst Technologies, Inc. is a Kansas City-based company specializing in advanced technology solutions that enhance operational efficiency and drive innovation across various sectors. The organization focuses on developing software and systems that facilitate data management, analytics, and cloud integration, catering to the needs of businesses seeking to leverage technology for improved decision-making and performance. With a commitment to research and development, Dst Technologies aims to provide cutting-edge solutions that address the evolving challenges of the digital landscape.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 27 2026

28 Patents

#22 in Kansas City, MO

#166 in Missouri

#12,022 in US

#23,317 in the World

Kansas City, MO, United States of America

Dst Technologies, Inc.

Forward Citations = 76

25 inventors:

Paul Martin Ives (10 out of 10 patents)

Peter E Clark (8 out of 8 patents)

Michael V Gentry (8 out of 8 patents)

4. Hui Peng Hu (7 out of 14 patents)

5. Ramesh Sridharan (5 out of 7 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Dst Technologies, Inc.. Retrieved from https://idiyas.com/company/dst-technologies

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

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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