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Four US patents. Five peer-reviewed papers. One of them in a journal with an impact factor of 8.9.

This is the part of the work that was reviewed by people with no commercial interest in the answer.

Why this page exists

Most companies selling AI services describe their capability. Very little of it has been examined by anyone outside the company.

This page is the opposite claim, and it is checkable. Every patent number below can be looked up at the USPTO. Every paper can be found at its publisher. The point is not that research credentials make better consultants — they do not, necessarily. The point is that when work has survived peer review and patent examination, you are not taking a vendor’s word for what they can do.

Patents

Four filings with the USPTO, two granted. All four are in the same technical area: tracking objects in motion and computing their position in real time.

Publication no. Status Date Title
US 11,565,166 B2 Granted 31 Jan 2023 Golf game implementation using ball tracking and scoring system
US 11,900,678 B2 Granted 13 Feb 2024 A system for tracking, locating and calculating the position of an object in a game involving moving objects
US 2023/0218971 A1 Published application 13 Jul 2023 A system for tracking, locating and predicting the position of a ball in a game of baseball or similar
US 2025/0029387 A1 Published application 23 Jan 2025 A system for tracking, locating and calculating the position of a first moving object in relation to a second object

Two of the four are granted. The other two are published applications, which means they have been filed and made public but not examined to a grant. They are listed as applications because that is what they are.

Peer-reviewed publications

Five papers, 2022 to 2023, across medical imaging, computational photography and software engineering practice.

Date Paper Published in Impact factor Citations
15 Sep 2023 AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge IEEE Transactions on Medical Imaging 8.9 17
29 Jun 2023 Relativistic GAN using Receptive Field Block for Single Image Super-Resolution ESDC International Symposium (IEEE SA) — —
07 May 2023 A Transformer-Based U-Net Architecture for Fast and Efficient Image Demoireing Computer Vision and Image Processing (Springer) — 41
18 Feb 2023 MIPI 2022 Challenge on Under-Display Camera Image Restoration Computer Vision – ECCV 2022 Workshops (Springer) — —
01 Aug 2022 Agile4MLS: Leveraging Agile Practices for Developing Machine Learning-Enabled Systems IEEE Software 3.3 2

The two that matter most, and they matter for different reasons.

The credibility anchor
AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge
15 September 2023 · IEEE Transactions on Medical Imaging
Read the paper page →
8.9
Impact factor
IEEE Transactions on Medical Imaging
17
Citations

IEEE Transactions on Medical Imaging is a top-tier venue, the challenge evaluated 14 teams against a dataset of roughly 113,000 images from 60,000 patients across 500 screening centres, and the best systems performed comparably to 20 expert ophthalmologists. Founding Minds people are among the authors.

The one that proves the positioning
Agile4MLS: Leveraging Agile Practices for Developing Machine Learning-Enabled Systems
1 August 2022 · IEEE Software
Impact factor 3.3 · 2 citations
Read the paper page →

It is published in IEEE Software, it is co-authored by Founding Minds’ own CEO alongside two university researchers, and its subject is how to actually run engineering when machine learning is inside the product. The claim elsewhere on this site is that AI is built into how the company delivers. This is that claim, peer-reviewed, four years before it became a marketing line.

The most-cited of the five

41
Citations
A Transformer-Based U-Net Architecture for Fast and Efficient Image Demoireing

The most-cited of the five, and the reason is efficiency, not novelty. Read the paper page.

The people behind the papers

Two names recur across the computer vision work: Densen Puthussery and Hrishikesh Panikkasseril Sethumadavan, who appear on four of the five. Akhil K.A co-authored the super-resolution paper. Agile4MLS has four authors, in published order: Karthik Vaidhyanathan, Anish Chandran, Henry Muccini and Regi Roy — two from Founding Minds, two from a university software-architecture group.

Where to start

The AI Modernization Assessment is two weeks and $5,000. Not a code audit. You get a prioritized roadmap, effort and cost ranges, and a written list of the workflows where AI would add risk without adding value.

Book the assessment