AIMC Topic: Neural Networks, Computer

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A method for feature division of Soccer Foul actions based on salience image semantics.

PloS one Jun 13, 2025
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...
Soccer Algorithms Deep Learning Image Processing, Computer-Assisted Video Recording Semantics Pattern Recognition, Automated Humans Neural Networks, Computer
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation.

PloS one Jun 13, 2025
INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...
Polysomnography Sleep Deprivation Adult Male Electroencephalography Signal Processing, Computer-Assisted Wavelet Analysis Neural Networks, Computer Algorithms Female Humans
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3D-MRI brain glioma intelligent segmentation based on improved 3D U-net network.

PloS one Jun 13, 2025
PURPOSE: To enhance glioma segmentation, a 3D-MRI intelligent glioma segmentation method based on deep learning is introduced. This method offers significant guidance for medical diagnosis, grading, and treatment strategy selection.
Humans Neural Networks, Computer Algorithms Glioma Magnetic Resonance Imaging Brain Neoplasms Deep Learning Imaging, Three-Dimensional
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Integrated Intelligent Material Recognition and Information Exchange Platform Based on a Highly Sensitive Flexible Pressure Sensor and Electroluminescent Display.

ACS sensors Jun 11, 2025
Flexible pressure sensors have become a research hotspot in human-computer interaction and material recognition due to their flexibility and high sensitivity. However, the identified information relies on traditional displays and cannot be dynamicall...
Neural Networks, Computer Equipment Design Pressure Humans
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Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Analytical chemistry Jun 11, 2025
Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprecedented detail. Virtual staining techniques, which rely on computational algorithms to map molecular ...
Humans Least-Squares Analysis Spectrum Analysis, Raman Multivariate Analysis Algorithms Collagen Lipids Neural Networks, Computer Hyperspectral Imaging Cell Line, Tumor Principal Component Analysis Machine Learning Staining and Labeling
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Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Analytical chemistry Jun 11, 2025
Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current clinical diagnosis relies on endoscopic biopsy and histopathological analysis, which are highly depende...
Neural Networks, Computer Stomach Neoplasms Deep Learning Humans Time Factors Spectrum Analysis, Raman
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Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.

Techniques in coloproctology Jun 11, 2025
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...
Ligation Male Humans Middle Aged Neural Networks, Computer Italy Deep Learning Female Postoperative Complications Colonic Neoplasms Databases, Factual Predictive Value of Tests Aged Colectomy Laparoscopy
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Implicit neural representation for medical image reconstruction.

Physics in medicine and biology Jun 11, 2025
Medical image reconstruction aims to generate high-quality images from incompletely sampled raw sensor data, which poses an ill-posed inverse problem. Traditional iterative reconstruction methods rely on prior information to empirically construct reg...
Neural Networks, Computer Humans Image Processing, Computer-Assisted Diagnostic Imaging
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POC-CSP: a novel parameterised and orthogonally-constrained neural network layer for learning common spatial patterns (CSP) in EEG signals.

Journal of neural engineering Jun 11, 2025
. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it has shortcomings including sensitivity to noise and rigidity in the value of the weights. Our goal wa...
Humans Neural Networks, Computer Machine Learning Adult Male Imagination Electroencephalography Brain-Computer Interfaces
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Tailored knowledge distillation with automated loss function learning.

PloS one Jun 11, 2025
Knowledge Distillation (KD) is one of the most effective and widely used methods for model compression of large models. It has achieved significant success with the meticulous development of distillation losses. However, most state-of-the-art KD loss...
Knowledge Distillation Machine Learning Humans Algorithms Neural Networks, Computer Learning
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