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From the 1 of 44 linked papers with an AI index.

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20242026
most citedPersonalized Weight Loss Management through Wearable Devices and Artificial Intelligence

1 citations · 1 across the 8 of their papers we have counts for

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cs.CV2026

VideoRun2D Demo: Markerless Body Tracking for Biomechanical Analysis of Running

Luis F. Gomez, Julian Fierrez, Roberto Daza +5

Human pose estimation has advanced significantly due to the development of deep learning models, increased data availability, and improved computing resources. These developments h…

cs.CV2026

Unraveling Machine Behavior by Multi-Level Bias Analysis and Detection: Methodology and Application to Computer Vision

Ignacio Serna, Aythami Morales, Julian Fierrez

This study investigates the presence and propagation of bias within Neural Networks through a comprehensive multi-level analysis spanning the learned latent space, layer activation…

cs.CV2026

Is My Vision-Language Data in Your AI? Membership Inference Test (MINT) Demo 2

Daniel DeAlcala, Gonzalo Mancera, Julian Fierrez +3

We present the Membership Inference Test (MINT) Demo 2, a framework designed to improve transparency in machine learning training processes. MINT is a technique for experimentally…

cs.CV2026

Exploring Deep Learning and Ultra-Widefield Imaging for Diabetic Retinopathy and Macular Edema

Pablo Jimenez-Lizcano, Sergio Romero-Tapiador, Ruben Tolosana +4

Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of preventable blindness among working-age adults. Traditional approaches in the literature focus on s…

cs.CV2026

Leveraging Avatar Fingerprinting: A Multi-Generator Photorealistic Talking-Head Public Database and Benchmark

Laura Pedrouzo-Rodriguez, Luis F. Gomez, Ruben Tolosana +4

Recent advances in photorealistic avatar generation have enabled highly realistic talking-head avatars, raising security concerns regarding identity impersonation in AI-mediated co…

cs.CV2026

Membership Inference Test: Auditing Training Data in Object Classification Models

Gonzalo Mancera, Daniel DeAlcala, Aythami Morales +2

In this research, we analyze the performance of Membership Inference Tests (MINT), focusing on determining whether given data were utilized during the training phase, specifically…