Artificial Intelligence Medical Compendium

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

Showing 22,671 to 22,680 of 216,842 articles

Tracing Like a Clinician: Anatomy-Guided Spatial Priors for Cephalometric Landmark Detection

arXiv May 5, 2026
When orthodontists trace cephalometric radiographs, they follow a structured workflow: identify the soft tissue profile, partition the skull into anatomical regions, trace contours, and locate landmarks using geometric definitions -- yet no automated... read more 
Computer Vision and Pattern Recognition

Dual-Foundation Models for Unsupervised Domain Adaptation

arXiv May 5, 2026
Semantic segmentation provides pixel-level scene understanding essential for autonomous driving and fine-grained perception tasks. However, training segmentation models requires costly, labor-intensive annotations on real-world datasets. Unsupervised... read more 
Computer Vision and Pattern Recognition

SoDa2: Single-Stage Open-Set Domain Adaptation via Decoupled Alignment for Cross-Scene Hyperspectral Image Classification

arXiv May 5, 2026
Cross-scene hyperspectral image (HSI) classification stands as a fundamental research topic in remote sensing, with extensive applications spanning various fields. Owing to the inclusion of unknown categories in the target domain and the existence of... read more 
Computer Vision and Pattern Recognition

Fully Automatic Trace Gas Plume Detection

arXiv May 5, 2026
Future imaging spectrometers will increase data volumes by orders of magnitude, requiring automated detection of trace gas point sources. We present a fully automated framework that combines machine learning-based morphological analysis with physics-... read more 
Machine Learning

Design and Implementation of BNN-Based Object Detection on FPGA

arXiv May 5, 2026
This paper implements a Binary Neural Network (BNN) based YOLOv3-tiny-like object detector on a low-cost FPGA. The network takes 320*320*3 RGB images as input. Its main convolution layers use 1-bit weights and 8-bit activations, while Conv1 and the f... read more 
Hardware Architecture

TsallisPGD: Adaptive Gradient Weighting for Adversarial Attacks on Semantic Segmentation

arXiv May 5, 2026
Attacking semantic segmentation models is significantly harder than image classification models because an attacker must flip thousands of pixel predictions simultaneously. Standard pixel-wise cross-entropy (CE) is ill-suited to this setting: it tend... read more 
Computer Vision and Pattern Recognition cs.LG

StreakMind: AI detection and analysis of satellite streaks in astronomical images with automated database integration

arXiv May 5, 2026
Artificial satellites and space debris increasingly contaminate astronomical images, affecting scientific surveys and producing large volumes of streaked exposures. Manual inspection is no longer feasible at scale, and reliable detection and characte... read more 
Instrumentation and Methods for Astrophysics cs.LG

MK-ResRecon: Multi-Kernel Residual Framework for Texture-Aware 3D MRI Refinement from Sparse 2D Slices

arXiv May 5, 2026
Magnetic Resonance Imaging (MRI) acquisition remains a time-intensive and patient-straining process, as prolonged scan dura- tions increase the likelihood of motion artifacts, which degrade image quality and frequently require repeated scans. To addr... read more 
Computer Vision and Pattern Recognition

Orientation-Aware Unsupervised Domain Adaptation for Brain Tumor Classification Across Multi-Modal MRI

arXiv May 5, 2026
The clinical integration of deep learning models for brain tumor diagnosis in neuro-oncology is severely constrained by limited expert-annotated MRI data and substantial inter-institutional domain shift arising from variations in scanners, imaging pr... read more 
Computer Vision and Pattern Recognition

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

arXiv May 5, 2026
We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a stream, the problems of computation and data storage arise for any graph-based method. We propose ... read more 
Machine Learning stat.ML
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