Traditional police combat training relies heavily on subjective evaluation by human instructors, which lacks consistency and comprehensive coverage of complex movement patterns in real-world scenarios. This paper presents an enhanced deep spatio-temp...
Recent advancements in deep learning have led to significant improvements in pneumoconiosis diagnosis from chest X-rays (CXR). However, these models typically require large training datasets, which are challenging to collect due to the rarity of the ...
This study aims to analyze the key factors contributing to victories in world women's volleyball matches and predict match win rates using machine learning algorithms. Initially, Grey Relational Analysis (GRA) was employed to analyze the fundamental ...
Human activity recognition (HAR) is essential for applications such as healthcare monitoring, fitness tracking, and smart environments, yet deploying accurate and interpretable models on resource-constrained devices remains challenging. In this paper...
Face recognition based on deep neural networks has achieved great success, but its application in resource-constrained and unconstrained scenarios, such as vehicle images from traffic monitoring systems, remains challenging. These scenarios involve c...
The longitudinal course of epilepsy remains largely unpredictable. This study aimed to predict final outcome and classify dynamic longitudinal trajectories using artificial intelligence. A total of 2586 patients who first visited our epilepsy special...
Recent advancements in precision agriculture have introduced innovative approaches to addressing plant stress, a critical factor influencing crop productivity and agricultural sustainability. Accurate, real-time prediction of plant stress has become ...
DNA molecules can be used to build "neural networks" that function like the brain, enabling them to perform complex computational tasks. However, a fundamental limitation of existing DNA networks is that their most basic computing units cannot perfor...
Biomedical physics & engineering express
Nov 27, 2025
Sparse-view low-dose computed tomography (LDCT) imaging poses difficulties in preserving image quality while reducing radiation exposure. Recent research has focused extensively on artificial intelligence (AI) to reduce artifacts in LDCT. This paper ...
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