Artificial Intelligence Medical Compendium

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

Showing 4,311 to 4,320 of 174,001 articles

Transfer learning optimization based on evolutionary selective fine tuning

arXiv Aug 21, 2025
Deep learning has shown substantial progress in image analysis. However, the computational demands of large, fully trained models remain a consideration. Transfer learning offers a strategy for adapting pre-trained models to new tasks. Traditional ... read more 
Computer Vision and Pattern Recognition

Glo-VLMs: Leveraging Vision-Language Models for Fine-Grained Diseased Glomerulus Classification

arXiv Aug 21, 2025
Vision-language models (VLMs) have shown considerable potential in digital pathology, yet their effectiveness remains limited for fine-grained, disease-specific classification tasks such as distinguishing between glomerular subtypes. The subtle mor... read more 
Computer Vision and Pattern Recognition

Active Learning for Neurosymbolic Program Synthesis

arXiv Aug 21, 2025
The goal of active learning for program synthesis is to synthesize the desired program by asking targeted questions that minimize user interaction. While prior work has explored active learning in the purely symbolic setting, such techniques are in... read more 
Programming Languages

High-Frequency First: A Two-Stage Approach for Improving Image INR

arXiv Aug 21, 2025
Implicit Neural Representations (INRs) have emerged as a powerful alternative to traditional pixel-based formats by modeling images as continuous functions over spatial coordinates. A key challenge, however, lies in the spectral bias of neural netw... read more 
Computer Vision and Pattern Recognition

Integrating frequency and dynamic characteristics of EMG signals as a new inter-muscular coordination feature.

Physical and engineering sciences in medicine Aug 21, 2025
The impairment of inter-muscular coordination and changes in frequency components are two major pathological symptoms associated with knee injuries; however, an effective method to simultaneously quantify these changes has yet to be developed. Moreov... read more 

CineScale: Free Lunch in High-Resolution Cinematic Visual Generation

arXiv Aug 21, 2025
Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data and constrained computation resources, hampering their ability to generate high-fidelity images or vi... read more 
Computer Vision and Pattern Recognition

CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps

arXiv Aug 21, 2025
Detailed 3D building models are crucial for urban planning, digital twins, and disaster management applications. While Level of Detail 1 (LoD)1 and LoD2 building models are widely available, they lack detailed facade elements essential for advanced... read more 
Computer Vision and Pattern Recognition Image and Video Processing

Waver: Wave Your Way to Lifelike Video Generation

arXiv Aug 21, 2025
We present Waver, a high-performance foundation model for unified image and video generation. Waver can directly generate videos with durations ranging from 5 to 10 seconds at a native resolution of 720p, which are subsequently upscaled to 1080p. T... read more 
Computer Vision and Pattern Recognition

Robust and Efficient Quantum Reservoir Computing with Discrete Time Crystal

arXiv Aug 21, 2025
The rapid development of machine learning and quantum computing has placed quantum machine learning at the forefront of research. However, existing quantum machine learning algorithms based on quantum variational algorithms face challenges in train... read more 
Quantum Physics Artificial Intelligence Machine Learning

SafeLLM: Unlearning Harmful Outputs from Large Language Models against Jailbreak Attacks

arXiv Aug 21, 2025
Jailbreak attacks pose a serious threat to the safety of Large Language Models (LLMs) by crafting adversarial prompts that bypass alignment mechanisms, causing the models to produce harmful, restricted, or biased content. In this paper, we propose ... read more 
Machine Learning
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