Artificial Intelligence Medical Compendium

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

Showing 30,521 to 30,530 of 220,100 articles

MaMe & MaRe: Matrix-Based Token Merging and Restoration for Efficient Visual Perception and Synthesis

arXiv Apr 15, 2026
Token compression is crucial for mitigating the quadratic complexity of self-attention mechanisms in Vision Transformers (ViTs), which often involve numerous input tokens. Existing methods, such as ToMe, rely on GPU-inefficient operations (e.g., sort... read more 
Computer Vision and Pattern Recognition cs.AI

A Study of Failure Modes in Two-Stage Human-Object Interaction Detection

arXiv Apr 15, 2026
Human-object interaction (HOI) detection aims to detect interactions between humans and objects in images. While recent advances have improved performance on existing benchmarks, their evaluations mainly focus on overall prediction accuracy and provi... read more 
Computer Vision and Pattern Recognition cs.AI

MyoVision: A Mobile Research Tool and NEATBoost-Attention Ensemble Framework for Real Time Chicken Breast Myopathy Detection

arXiv Apr 15, 2026
Woody Breast (WB) and Spaghetti Meat (SM) myopathies significantly impact poultry meat quality, yet current detection methods rely either on subjective manual evaluation or costly laboratory-grade imaging systems. We address the problem of low-cost, ... read more 
Machine Learning cs.CV

Learning Class Difficulty in Imbalanced Histopathology Segmentation via Dynamic Focal Attention

arXiv Apr 15, 2026
Semantic segmentation of histopathology images under class imbalance is typically addressed through frequency-based loss reweighting, which implicitly assumes that rare classes are difficult. However, true difficulty also arises from morphological va... read more 
Image and Video Processing cs.CV

Joint Representation Learning and Clustering via Gradient-Based Manifold Optimization

arXiv Apr 15, 2026
Clustering and dimensionality reduction have been crucial topics in machine learning and computer vision. Clustering high-dimensional data has been challenging for a long time due to the curse of dimensionality. For that reason, a more promising dire... read more 
Machine Learning cs.LG

Enhanced Text-to-Image Generation by Fine-grained Multimodal Reasoning

arXiv Apr 15, 2026
With the rapid progress of Multimodal Large Language Models (MLLMs), unified MLLMs that jointly perform image understanding and generation have advanced significantly. However, despite the inherent reasoning capabilities of unified MLLMs for self-ref... read more 
Computer Vision and Pattern Recognition

ADP-DiT: Text-Guided Diffusion Transformer for Brain Image Generation in Alzheimer's Disease Progression

arXiv Apr 15, 2026
Alzheimer's disease (AD) progresses heterogeneously across individuals, motivating subject-specific synthesis of follow-up magnetic resonance imaging (MRI) to support progression assessment. While Diffusion Transformers (DiT), an emerging transformer... read more 
Computer Vision and Pattern Recognition

DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer

arXiv Apr 15, 2026
Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization holds important research value in areas such as immersive applications and artistic creation, attra... read more 
Computer Vision and Pattern Recognition

Representation over Routing: Overcoming Surrogate Hacking in Multi-Timescale PPO

arXiv Apr 15, 2026
Temporal credit assignment in reinforcement learning has long been a central challenge. Inspired by the multi-timescale encoding of the dopamine system in neurobiology, recent research has sought to introduce multiple discount factors into Actor-Crit... read more 
Machine Learning cs.AI

From Alignment to Prediction: A Study of Self-Supervised Learning and Predictive Representation Learning

arXiv Apr 15, 2026
Self-supervised learning has emerged as a major technique for the task of learning from unlabeled data, where the current methods mostly revolve around alignment of representations and input recon struction. Although such approaches have demonstrated... read more 
Machine Learning cs.AI
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