AIMC Topic: Convolutional Neural Networks

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Reliability of Emotion Analysis from Human Facial Expressions Using Multi-task Cascaded Convolutional Neural Networks.

The journal of medical investigation : JMI Jan 1, 2025
Life support robots in care settings must be able to read a person's emotions from facial expressions to achieve empathic communication. This study aims to determine the degree of agreement between Multi-task Cascaded Convolutional Neural Networks (M...
Facial Expression Convolutional Neural Networks Emotions Female Reproducibility of Results Adult Male Young Adult Humans Neural Networks, Computer
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SVMVGGNet-16: A Novel Machine and Deep Learning Based Approaches for Lung Cancer Detection Using Combined SVM and VGGNet-16.

Current medical imaging Jan 1, 2025
BACKGROUND AND OBJECTIVE: Lung cancer remains a leading cause of cancer-related mortality worldwide, necessitating early and accurate detection methods. Our study aims to enhance lung cancer detection by integrating VGGNet-16 form of Convolutional Ne...
Humans Neural Networks, Computer Convolutional Neural Networks Lung Neoplasms Support Vector Machine Reproducibility of Results Deep Learning Tomography, X-Ray Computed
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Integrating single-cell multimodal epigenomic data using 1D convolutional neural networks.

Bioinformatics (Oxford, England) Dec 26, 2024
MOTIVATION: Recent experimental developments enable single-cell multimodal epigenomic profiling, which measures multiple histone modifications and chromatin accessibility within the same cell. Such parallel measurements provide exciting new opportuni...
Neural Networks, Computer Animals Convolutional Neural Networks Humans Epigenomics Single-Cell Analysis Mice
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[Coronary artery segmentation based on Transformer and convolutional neural networks dual parallel branch encoder neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2024
Manual segmentation of coronary arteries in computed tomography angiography (CTA) images is inefficient, and existing deep learning segmentation models often exhibit low accuracy on coronary artery images. Inspired by the Transformer architecture, th...
Deep Learning Convolutional Neural Networks Image Processing, Computer-Assisted Coronary Angiography Imaging, Three-Dimensional Humans Neural Networks, Computer Algorithms Coronary Vessels Computed Tomography Angiography
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[Image reconstruction for cerebral hemorrhage based on improved densely-connected fully convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2024
Cerebral hemorrhage is a serious cerebrovascular disease with high morbidity and high mortality, for which timely diagnosis and treatment are crucial. Electrical impedance tomography (EIT) is a functional imaging technique which is able to detect abn...
Image Processing, Computer-Assisted Cerebral Hemorrhage Convolutional Neural Networks Humans Phantoms, Imaging Neural Networks, Computer Electric Impedance Tomography Brain
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[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2024
This study aims to address the limitations in gesture recognition caused by the susceptibility of temporal and frequency domain feature extraction from surface electromyography signals, as well as the low recognition rates of conventional classifiers...
Gestures Signal Processing, Computer-Assisted Pattern Recognition, Automated Electromyography Machine Learning Algorithms Convolutional Neural Networks Humans Neural Networks, Computer
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[Three-dimensional convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery electroencephalography signal].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2024
The brain-computer interface (BCI) based on motor imagery electroencephalography (EEG) shows great potential in neurorehabilitation due to its non-invasive nature and ease of use. However, motor imagery EEG signals have low signal-to-noise ratios and...
Convolutional Neural Networks Electroencephalography Signal Processing, Computer-Assisted Neural Networks, Computer Brain Imagination Brain-Computer Interfaces Humans
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VirDetect-AI: a residual and convolutional neural network-based metagenomic tool for eukaryotic viral protein identification.

Briefings in bioinformatics Nov 22, 2024
This study addresses the challenging task of identifying viruses within metagenomic data, which encompasses a broad array of biological samples, including animal reservoirs, environmental sources, and the human body. Traditional methods for virus ide...
Neural Networks, Computer Artificial Intelligence Convolutional Neural Networks Humans Viruses Eukaryota Genome, Viral Computational Biology Viral Proteins Metagenomics Metagenome
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Large-scale parameters framework with large convolutional kernel for encoding visual fMRI activity information.

Cerebral cortex (New York, N.Y. : 1991) Jul 3, 2024
Visual encoding models often use deep neural networks to describe the brain's visual cortex response to external stimuli. Inspired by biological findings, researchers found that large receptive fields built with large convolutional kernels improve co...
Nerve Net Convolutional Neural Networks Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Vision, Ocular
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Residual Neural Networks for the Prediction of the Regularization Parameters in PET Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Positron Emission Tomography (PET) is a medical imaging modality relying on numerical methods that integrate the statistical properties of the measurements and prior assumptions about the images. In order to maximize the computed image quality, PET r...
Positron-Emission Tomography Algorithms Humans Convolutional Neural Networks Neural Networks, Computer Image Processing, Computer-Assisted
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