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From the 1 of 10 linked papers with an AI index.

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10 papers

cs.HC2026

Human-Centered Explainable AI for TinyML Edge Devices: A Pareto-Based Selection Framework with LLM-Guided Design

Zeinab Dehghani, Dhavalkumar Thakker, Koorosh Aslansefat +4

Edge Artificial Intelligence (Edge AI) enables the deployment of AI models directly on local edge devices, while such deployments are subject to strict resource constraints, partic…

cs.CV2026

Data Safety: Synthetic Data Quality Analysis Using CIFAKE Dataset

Kuniko Paxton, Amila Akagić, Koorosh Aslansefat +2

The paper examines how synthetic images generated by different methods differ from real images in feature space, color statistics, and model training, and proposes strategies for e…

cs.CV2026

Exploring the Impact of Skin Color on Skin Lesion Segmentation

Kuniko Paxton, Medina Kapo, Amila Akagić +3

Skin cancer, particularly melanoma, remains a major cause of morbidity and mortality, making early detection critical. AI-driven dermatology systems often rely on skin lesion segme…

cs.LG2026

EcoFair: Trustworthy and Energy-Aware Routing for Privacy-Preserving Vertically Partitioned Medical Inference

Mostafa Anoosha, Dhavalkumar Thakker, Kuniko Paxton +4

Privacy-preserving medical inference must balance data locality, diagnostic reliability, and deployment efficiency. This paper presents EcoFair, a simulated vertically partitioned…

cs.LG2025

HybridVFL: Disentangled Feature Learning for Edge-Enabled Vertical Federated Multimodal Classification

Mostafa Anoosha, Zeinab Dehghani, Kuniko Paxton +2

Vertical Federated Learning (VFL) offers a privacy-preserving paradigm for Edge AI scenarios like mobile health diagnostics, where sensitive multimodal data reside on distributed,…

cs.CV2025

Skewness-Guided Pruning of Multimodal Swin Transformers for Federated Skin Lesion Classification on Edge Devices

Kuniko Paxton, Koorosh Aslansefat, Dhavalkumar Thakker +1

In recent years, high-performance computer vision models have achieved remarkable success in medical imaging, with some skin lesion classification systems even surpassing dermatolo…