Artificial Intelligence Medical Compendium

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

Showing 20,031 to 20,040 of 215,962 articles

Multimodal Abstractive Summarization of Instructional Videos with Vision-Language Models

arXiv
Multimodal video summarization requires visual features that align semantically with language generation. Traditional approaches rely on CNN features trained for object classification, which represent visual concepts as discrete categories not aligne... read more 

Chronicles-OCR: A Cross-Temporal Perception Benchmark for the Evolutionary Trajectory of Chinese Characters

arXiv
Vision Large Language Models (VLLMs) have achieved remarkable success in modern text-rich visual understanding. However, their perceptual robustness in the face of the continuous morphological evolution of historical writing systems remains largely u... read more 

What Does It Mean for a Medical AI System to Be Right?

arXiv
This paper examines what it means for a medical AI system to be right by grounding the question in a specific clinical context: the automatic classification of plasma cells in digitized bone marrow smears for the diagnosis of multiple myeloma. Drawin... read more 

Optimizing 4D Wires for Sparse 3D Abstraction

arXiv
We present a unified framework for 3D geometric abstraction using a single continuous 4D wire, parameterized as a B-spline with spatial coordinates and variable width $(x,y,z,w)$. Existing approaches typically represent shapes as collections of many ... read more 

A Transfer Learning Evaluation of Deep Neural Networks for Image Classification

arXiv
Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages in achievin... read more 

EDGER: EDge-Guided with HEatmap Refinement for Generalizable Image Forgery Localization

arXiv
Text-guided inpainting has made image forgery increasingly realistic, challenging both SID and IFL. However, existing methods often struggle to point out suspicious signals across domains. To address this problem, we propose EDGER, a patch-based, dua... read more 

L2P: Unlocking Latent Potential for Pixel Generation

arXiv
Pixel diffusion models have recently regained attention for visual generation. However, training advanced pixel-space models from scratch demands prohibitive computational and data resources. To address this, we propose the Latent-to-Pixel (L2P) tran... read more 

FAME: Feature Activation Map Explanation on Image Classification and Face Recognition

arXiv
Deep Learning has revolutionized machine learning, reaching unprecedented levels of accuracy, but at the cost of reduced interpretability. Especially in image processing systems, deep networks transform local pixel information into more global concep... read more 

What-Where Transformer: A Slot-Centric Visual Backbone for Concurrent Representation and Localization

arXiv
Many image understanding tasks involve identifying what is present and where it appears. However, tasks that address where, such as object discovery, detection, and segmentation, are often considerably more complex than image classification, which pr... read more 

Spectral Vision Transformer for Efficient Tokenization with Limited Data

arXiv
We propose a novel spectral vision transformer architecture for efficient tokenization in limited data, with an emphasis on medical imaging. We outline convenient theoretical properties arising from the choice of basis including spatial invariance an... read more