Artificial Intelligence Medical Compendium

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

Showing 35,191 to 35,200 of 222,841 articles

Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition

arXiv Apr 7, 2026
Extracting vehicle information from surveillance images is essential for intelligent transportation systems, enabling applications such as traffic monitoring and criminal investigations. While Automatic License Plate Recognition (ALPR) is widely used... read more 
Computer Vision and Pattern Recognition

Final Report, Center for Computer-Integrated Computer-Integrated Surgical Systems and Technology, NSF ERC Cooperative Agreement EEC9731748, Volume 1

arXiv Apr 7, 2026
In the last ten years, medical robotics has moved from the margins to the mainstream. Since the Engineering Research Center for Computer-Integrated Surgical Systems and Technology was Launched in 1998 with National Science Foundation funding, medical... read more 
Robotics cs.CV

From Measurement to Mitigation: Quantifying and Reducing Identity Leakage in Image Representation Encoders with Linear Subspace Removal

arXiv Apr 7, 2026
Frozen visual embeddings (e.g., CLIP, DINOv2/v3, SSCD) power retrieval and integrity systems, yet their use on face-containing data is constrained by unmeasured identity leakage and a lack of deployable mitigations. We take an attacker-aware view and... read more 
Computer Vision and Pattern Recognition

VLA-InfoEntropy: A Training-Free Vision-Attention Information Entropy Approach for Vision-Language-Action Models Inference Acceleration and Success

arXiv Apr 7, 2026
Vision-Language-Action (VLA) models integrate visual perception, language understanding, and action decision-making for cross-modal semantic alignment, exhibiting broad application potential. However, the joint processing of high-dimensional visual f... read more 
Computer Vision and Pattern Recognition cs.RO

CI-ICM: Channel Importance-driven Learned Image Coding for Machines

arXiv Apr 7, 2026
Traditional human vision-centric image compression methods are suboptimal for machine vision centric compression due to different visual properties and feature characteristics. To address this problem, we propose a Channel Importance-driven learned I... read more 
Image and Video Processing cs.CV cs.MM

AnyImageNav: Any-View Geometry for Precise Last-Meter Image-Goal Navigation

arXiv Apr 7, 2026
Image Goal Navigation (ImageNav) is evaluated by a coarse success criterion, the agent must stop within 1m of the target, which is sufficient for finding objects but falls short for downstream tasks such as grasping that require precise positioning. ... read more 
Robotics cs.CV

Beyond Semantic Search: Towards Referential Anchoring in Composed Image Retrieval

arXiv Apr 7, 2026
Composed Image Retrieval (CIR) has demonstrated significant potential by enabling flexible multimodal queries that combine a reference image and modification text. However, CIR inherently prioritizes semantic matching, struggling to reliably retrieve... read more 
Computer Vision and Pattern Recognition cs.MM

LSGS-Loc: Towards Robust 3DGS-Based Visual Localization for Large-Scale UAV Scenarios

arXiv Apr 7, 2026
Visual localization in large-scale UAV scenarios is a critical capability for autonomous systems, yet it remains challenging due to geometric complexity and environmental variations. While 3D Gaussian Splatting (3DGS) has emerged as a promising scene... read more 
Computer Vision and Pattern Recognition cs.RO

CRISP: Rank-Guided Iterative Squeezing for Robust Medical Image Segmentation under Domain Shift

arXiv Apr 7, 2026
Distribution shift in medical imaging remains a central bottleneck for the clinical translation of medical AI. Failure to address it can lead to severe performance degradation in unseen environments and exacerbate health inequities. Existing methods ... read more 
Computer Vision and Pattern Recognition

Few-Shot Semantic Segmentation Meets SAM3

arXiv Apr 7, 2026
Few-Shot Semantic Segmentation (FSS) focuses on segmenting novel object categories from only a handful of annotated examples. Most existing approaches rely on extensive episodic training to learn transferable representations, which is both computatio... read more 
Computer Vision and Pattern Recognition
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