Artificial Intelligence Medical Compendium

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

Showing 56,601 to 56,610 of 226,846 articles

Gaussian Belief Propagation Network for Depth Completion

arXiv Jan 29, 2026
Depth completion aims to predict a dense depth map from a color image with sparse depth measurements. Although deep learning methods have achieved state-of-the-art (SOTA), effectively handling the sparse and irregular nature of input depth data in de... read more 
Computer Vision and Pattern Recognition

Mam-App: A Novel Parameter-Efficient Mamba Model for Apple Leaf Disease Classification

arXiv Jan 29, 2026
The rapid growth of the global population, alongside exponential technological advancement, has intensified the demand for food production. Meeting this demand depends not only on increasing agricultural yield but also on minimizing food loss caused ... read more 
Computer Vision and Pattern Recognition

Adversarial Vulnerability Transcends Computational Paradigms: Feature Engineering Provides No Defense Against Neural Adversarial Transfer

arXiv Jan 29, 2026
Deep neural networks are vulnerable to adversarial examples--inputs with imperceptible perturbations causing misclassification. While adversarial transfer within neural networks is well-documented, whether classical ML pipelines using handcrafted fea... read more 
Machine Learning cs.AI cs.CV

Do Pathology Foundation Models Encode Disease Progression? A Pseudotime Analysis of Visual Representations

arXiv Jan 29, 2026
Vision foundation models trained on discretely sampled images achieve strong performance on classification benchmarks, yet whether their representations encode the continuous processes underlying their training data remains unclear. This question is ... read more 
Computer Vision and Pattern Recognition

SR$^{2}$-Net: A General Plug-and-Play Model for Spectral Refinement in Hyperspectral Image Super-Resolution

arXiv Jan 29, 2026
HSI-SR aims to enhance spatial resolution while preserving spectrally faithful and physically plausible characteristics. Recent methods have achieved great progress by leveraging spatial correlations to enhance spatial resolution. However, these meth... read more 
Computer Vision and Pattern Recognition

Memorization Control in Diffusion Models from Denoising-centric Perspective

arXiv Jan 29, 2026
Controlling memorization in diffusion models is critical for applications that require generated data to closely match the training distribution. Existing approaches mainly focus on data centric or model centric modifications, treating the diffusion ... read more 
Machine Learning cs.AI

Graph-Free Root Cause Analysis

arXiv Jan 29, 2026
Failures in complex systems demand rapid Root Cause Analysis (RCA) to prevent cascading damage. Existing RCA methods that operate without dependency graph typically assume that the root cause having the highest anomaly score. This assumption fails wh... read more 
Machine Learning cs.SE

Towards Geometry-Aware and Motion-Guided Video Human Mesh Recovery

arXiv Jan 29, 2026
Existing video-based 3D Human Mesh Recovery (HMR) methods often produce physically implausible results, stemming from their reliance on flawed intermediate 3D pose anchors and their inability to effectively model complex spatiotemporal dynamics. To o... read more 
Computer Vision and Pattern Recognition

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

arXiv Jan 29, 2026
Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to create a cycle where understanding and generation mutually reinforce each other. While recent post-training... read more 
Computer Vision and Pattern Recognition cs.LG

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

arXiv Jan 29, 2026
Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to create a cycle where understanding and generation mutually reinforce each other. While recent post-training... read more 
Computer Vision and Pattern Recognition cs.LG
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