Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 45,011 to 45,020 of 224,055 articles

InstMeter: An Instruction-Level Method to Predict Energy and Latency of DL Model Inference on MCUs

arXiv Mar 4, 2026
Deep learning (DL) models can now run on microcontrollers (MCUs). Through neural architecture search (NAS), we can search DL models that meet the constraints of MCUs. Among various constraints, energy and latency costs of the model inference are crit... read more 
Machine Learning

A Multi-Agent Framework for Interpreting Multivariate Physiological Time Series

arXiv Mar 4, 2026
Continuous physiological monitoring is central to emergency care, yet deploying trustworthy AI is challenging. While LLMs can translate complex physiological signals into clinical narratives, it is unclear how agentic systems perform relative to zero... read more 
Machine Learning

LISTA-Transformer Model Based on Sparse Coding and Attention Mechanism and Its Application in Fault Diagnosis

arXiv Mar 4, 2026
Driven by the continuous development of models such as Multi-Layer Perceptron, Convolutional Neural Network (CNN), and Transformer, deep learning has made breakthrough progress in fields such as computer vision and natural language processing, and ha... read more 
Computer Vision and Pattern Recognition

Degradation-based augmented training for robust individual animal re-identification

arXiv Mar 4, 2026
Wildlife re-identification aims to recognise individual animals by matching query images to a database of previously identified individuals, based on their fine-scale unique morphological characteristics. Current state-of-the-art models for multispec... read more 
Computer Vision and Pattern Recognition

NOVA3R: Non-pixel-aligned Visual Transformer for Amodal 3D Reconstruction

arXiv Mar 4, 2026
We present NOVA3R, an effective approach for non-pixel-aligned 3D reconstruction from a set of unposed images in a feed-forward manner. Unlike pixel-aligned methods that tie geometry to per-ray predictions, our formulation learns a global, view-agnos... read more 
Computer Vision and Pattern Recognition

NOVA3R: Non-pixel-aligned Visual Transformer for Amodal 3D Reconstruction

arXiv Mar 4, 2026
We present NOVA3R, an effective approach for non-pixel-aligned 3D reconstruction from a set of unposed images in a feed-forward manner. Unlike pixel-aligned methods that tie geometry to per-ray predictions, our formulation learns a global, view-agnos... read more 
Computer Vision and Pattern Recognition

REDNET-ML: A Multi-Sensor Machine Learning Pipeline for Harmful Algal Bloom Risk Detection Along the Omani Coast

arXiv Mar 4, 2026
Harmful algal blooms (HABs) can threaten coastal infrastructure, fisheries, and desalination dependent water supplies. This project (REDNET-ML) develops a reproducible machine learning pipeline for HAB risk detection along the Omani coastline using m... read more 
Machine Learning

Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means

arXiv Mar 4, 2026
Density aggregation is a central problem in machine learning, for instance when combining predictions from a Deep Ensemble. The choice of aggregation remains an open question with two commonly proposed approaches being linear pooling (probability ave... read more 
Machine Learning cs.CV cs.LG math.ST stat.ME

Real5-OmniDocBench: A Full-Scale Physical Reconstruction Benchmark for Robust Document Parsing in the Wild

arXiv Mar 4, 2026
While Vision-Language Models (VLMs) achieve near-perfect scores on digital document benchmarks like OmniDocBench, their performance in the unpredictable physical world remains largely unknown due to the lack of controlled yet realistic evaluations. W... read more 
Computer Vision and Pattern Recognition

Semi-Supervised Generative Learning via Latent Space Distribution Matching

arXiv Mar 4, 2026
We introduce Latent Space Distribution Matching (LSDM), a novel framework for semi-supervised generative modeling of conditional distributions. LSDM operates in two stages: (i) learning a low-dimensional latent space from both paired and unpaired dat... read more 
Machine Learning cs.LG
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