Artificial Intelligence Medical Compendium

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

Showing 60,331 to 60,340 of 228,072 articles

IceWatch: Forecasting Glacial Lake Outburst Floods (GLOFs) using Multimodal Deep Learning

arXiv Jan 18, 2026
Glacial Lake Outburst Floods (GLOFs) pose a serious threat in high mountain regions. They are hazardous to communities, infrastructure, and ecosystems further downstream. The classical methods of GLOF detection and prediction have so far mainly relie... read more 
Machine Learning cs.AI

Turbo-GoDec: Exploiting the Cluster Sparsity Prior for Hyperspectral Anomaly Detection

arXiv Jan 18, 2026
As a key task in hyperspectral image processing, hyperspectral anomaly detection has garnered significant attention and undergone extensive research. Existing methods primarily relt on two prior assumption: low-rank background and sparse anomaly, alo... read more 
Computer Vision and Pattern Recognition

MMDeepResearch-Bench: A Benchmark for Multimodal Deep Research Agents

arXiv Jan 18, 2026
Deep Research Agents (DRAs) generate citation-rich reports via multi-step search and synthesis, yet existing benchmarks mainly target text-only settings or short-form multimodal QA, missing end-to-end multimodal evidence use. We introduce MMDeepResea... read more 
Computer Vision and Pattern Recognition

SimpleMatch: A Simple and Strong Baseline for Semantic Correspondence

arXiv Jan 18, 2026
Recent advances in semantic correspondence have been largely driven by the use of pre-trained large-scale models. However, a limitation of these approaches is their dependence on high-resolution input images to achieve optimal performance, which resu... read more 
Computer Vision and Pattern Recognition cs.AI

DepthCropSeg++: Scaling a Crop Segmentation Foundation Model With Depth-Labeled Data

arXiv Jan 18, 2026
DepthCropSeg++: a foundation model for crop segmentation, capable of segmenting different crop species under open in-field environment. Crop segmentation is a fundamental task for modern agriculture, which closely relates to many downstream tasks suc... read more 
Computer Vision and Pattern Recognition

CD-TWINSAFE: A ROS-enabled Digital Twin for Scene Understanding and Safety Emerging V2I Technology

arXiv Jan 18, 2026
In this paper, the CD-TWINSAFE is introduced, a V2I-based digital twin for Autonomous Vehicles. The proposed architecture is composed of two stacks running simultaneously, an on-board driving stack that includes a stereo camera for scene understandin... read more 
Computer Vision and Pattern Recognition cs.HC cs.RO

Utilizing the Score of Data Distribution for Hyperspectral Anomaly Detection

arXiv Jan 18, 2026
Hyperspectral images (HSIs) are a type of image that contains abundant spectral information. As a type of real-world data, the high-dimensional spectra in hyperspectral images are actually determined by only a few factors, such as chemical compositio... read more 
Computer Vision and Pattern Recognition

Multimodal Spatial Omics: From Data Acquisition to Computational Integration

arXiv Jan 18, 2026
Recent developments in spatial omics technologies have enabled the generation of high dimensional molecular data, such as transcriptomes, proteomes, and epigenomes, within their spatial tissue context, either through coprofiling on the same slice or ... read more 
Quantitative Methods q-bio.BM q-bio.GN

A Hierarchical Benchmark of Foundation Models for Dermatology

arXiv Jan 18, 2026
Foundation models have transformed medical image analysis by providing robust feature representations that reduce the need for large-scale task-specific training. However, current benchmarks in dermatology often reduce the complex diagnostic taxonomy... read more 
Computer Vision and Pattern Recognition

Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Versatile Image Generation

arXiv Jan 18, 2026
Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning large-scale generative models, such as diffusion and flow models, to align with complex human preferences and user-specified tasks. A fundamental limitation remains \texti... read more 
Machine Learning cs.AI
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