Signals 4 · free daily AI digest

Uncertainty-Aware Federated Learning for Infant Movement Analysis

Paper recorded by Signals 4 on 2026-09-25 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28

Category: cs.AI · 人工智能 · first seen 2026-09-28

Abstract

Infant movement analysis provides valuable biomarkers for the early identification of neurodevelopmental disorders. Recent advances in deep learning have enabled automated analysis of infant movements from video-derived skeletal representations, achieving performance comparable to expert assessment for tasks such as General Movement Assessment (GMA). However, most existing approaches rely on centr

Read on arXiv →

#17 most recent of 420 cs.AI papers we have recorded · ↑ newer: PriceBench: A Diagnostic Benchmark for Price, Quality, and Brand Prefe · ↓ older: Segment-Level Agentic Topic Modeling for Improved Data Exploration and
Cite this page: Uncertainty-Aware Federated Learning for Infant Movement Analysis: the #17 most recent of 420 cs.AI papers we have recorded (as of 2026-09-25). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/uncertainty-aware-federated-learning-for-infant-movement-analysis.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions