Artificial Intelligence Medical Compendium

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

Showing 25,451 to 25,460 of 217,759 articles

JSSFF: A Joint Structural-Semantic Fusion Framework for Remote Sensing Image Captioning

arXiv Apr 27, 2026
The encoder-decoder framework has become widely popular nowadays. In this model, the encoder extracts informative visual features from an input image, and the decoder employs a sequence-to-sequence formulation to generate the corresponding textual de... read more 
Computer Vision and Pattern Recognition

CLLAP: Contrastive Learning-based LiDAR-Augmented Pretraining for Enhanced Radar-Camera Fusion

arXiv Apr 27, 2026
Accurate 3D object detection is critical for autonomous driving, necessitating reliable, cost-effective sensors capable of operating in adverse weather conditions. Camera and millimeter-wave radar fusion has emerged as a promising solution; however, ... read more 
Computer Vision and Pattern Recognition

Meta-Ensemble Learning with Diverse Data Splits for Improved Respiratory Sound Classification

arXiv Apr 27, 2026
Training reliable respiratory sound classification models remains challenging due to the limited size and subject diversity of datasets. Ensemble methods can improve robustness, but when base models are trained on identical data, models tend to overf... read more 
Machine Learning cs.AI

SemiSAM-O1: How far can we push the boundary of annotation-efficient medical image segmentation?

arXiv Apr 27, 2026
Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation models. While recent advances in foundation model-driven SSL have pushed the boundary to extremely lim... read more 
Computer Vision and Pattern Recognition

Open-Vocabulary Semantic Segmentation Network Integrating Object-Level Label and Scene-Level Semantic Features for Multimodal Remote Sensing Images

arXiv Apr 27, 2026
Semantic segmentation of multi-modal remote sensing imagery plays a pivotal role in land use/land cover (LULC) mapping, environmental monitoring, and precision earth observation. Current multi-modal approaches mainly focus on integrating complementar... read more 
Computer Vision and Pattern Recognition

Psychologically-Grounded Graph Modeling for Interpretable Depression Detection

arXiv Apr 27, 2026
Automatic depression detection from conversational interactions holds significant promise for scalable screening but remains hindered by severe data scarcity and a lack of clinical interpretability. Existing approaches typically rely on black-box dee... read more 
Computation and Language

Bridging Restoration and Generation Manifolds in One-Step Diffusion for Real-World Super-Resolution

arXiv Apr 27, 2026
Pretrained diffusion models have revolutionized real-world image super-resolution (Real-ISR) but suffer from computational bottlenecks due to iterative sampling. Recent single-step distillation accelerates inference but faces a stark perception-disto... read more 
Computer Vision and Pattern Recognition eess.IV

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

arXiv Apr 27, 2026
Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imaging increasingly exceed what can be addressed by scan-level prediction alone. Clinically useful AI f... read more 
Computer Vision and Pattern Recognition

6thGrid-Net: Unified Remote Sensing Image Dehazing Based on Color Restoration and Edge-Preserving

arXiv Apr 27, 2026
Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications. Existing restoration methods typically rely on computationally heavy architectures or sequential... read more 
Computer Vision and Pattern Recognition

Progressive Approximation in Deep Residual Networks: Theory and Validation

arXiv Apr 27, 2026
The Universal Approximation Theorem (UAT) guarantees universal function approximation but does not explain how residual models distribute approximation across layers. We reframe residual networks as a layer-wise approximation process that builds an a... read more 
Machine Learning cs.AI
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