AIMC Topic: Convolutional Neural Networks

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Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

PloS one Jun 17, 2025
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variabi...
Humans Neural Networks, Computer Deep Learning Convolutional Neural Networks Electrocardiography Algorithms Databases, Factual Signal Processing, Computer-Assisted Arrhythmias, Cardiac
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FFLUNet: Feature Fused Lightweight UNet for brain tumor segmentation.

Computers in biology and medicine Jun 14, 2025
Brain tumors, particularly glioblastoma multiforme, are considered one of the most threatening types of tumors in neuro-oncology. Segmenting brain tumors is a crucial part of medical imaging. It plays a key role in diagnosing conditions, planning tre...
Brain Neoplasms Deep Learning Convolutional Neural Networks Humans Glioblastoma Image Interpretation, Computer-Assisted Software Validation Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

PloS one Jun 9, 2025
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...
Myocardium Heart Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Cicatrix Middle Aged Convolutional Neural Networks Machine Learning Humans Algorithms Neural Networks, Computer Aged Male Female
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Validation of simulated training sets using a convolutional neural network for isotope identification in urban environments.

PloS one Jun 9, 2025
Real-time isotope identification in urban environments can aid law enforcement by providing additional information about the nature of a potential threat. Neural networks have shown promise in isotope identification but the large range of potential i...
Isotopes Convolutional Neural Networks Cities Neural Networks, Computer Computer Simulation
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Towards sustainable solutions: Effective waste classification framework via enhanced deep convolutional neural networks.

PloS one Jun 4, 2025
As industrialization and the development of smart cities progress, effective waste collection, classification, and management have become increasingly vital. Recycling processes depend on accurately identifying and restoring waste materials to their ...
Recycling Neural Networks, Computer Waste Management Deep Learning Convolutional Neural Networks
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Gradient-driven pixel connectivity convolutional neural networks classification based on U-Net lung nodule segmentation.

Medical engineering & physics Jun 3, 2025
Lung cancer is a significant global health issue, heavily burdening healthcare systems. Early detection is crucial for improving patient outcomes. This study proposes a diagnostic aid system for the early detection and classification of lung nodules ...
Lung Neoplasms Tomography, X-Ray Computed Humans Lung Neural Networks, Computer Convolutional Neural Networks Deep Learning Image Processing, Computer-Assisted
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Ultra-High-Resolution Photon-Counting-Detector CT with a Dedicated Denoising Convolutional Neural Network for Enhanced Temporal Bone Imaging.

AJNR. American journal of neuroradiology Jun 3, 2025
BACKGROUND AND PURPOSE: Ultra-high-resolution (UHR) photon-counting-detector (PCD) CT improves image resolution but increases noise, necessitating the use of smoother reconstruction kernels that reduce resolution below the 0.125-mm maximum spatial re...
Humans Neural Networks, Computer Convolutional Neural Networks Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Temporal Bone Signal-To-Noise Ratio Photons
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Image key information processing using convolutional neural network and rotational invariant-hierarchical max pooling algorithm.

PloS one May 27, 2025
In the information age, the effectiveness of image processing determines the quality of a large number of image analysis tasks. A fusion algorithm-based processing technique was proposed to process key image information. A feature dictionary was intr...
Humans Convolutional Neural Networks Image Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Non-proliferative diabetic retinopathy detection using Rosmarus Quagga optimized explainable generative meta learning based deep convolutional neural network model.

International ophthalmology May 8, 2025
PURPOSE: Non-Proliferative Diabetic Retinopathy (NPDR) is a complication of diabetes disease where there is damage of the blood vessels in retina but with no signs of formation of new vessels. It is present in the earlier stages and therefore the con...
Convolutional Neural Networks Humans Neural Networks, Computer Retina Diabetic Retinopathy Deep Learning
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Identification of medicinal plant parts using depth-wise separable convolutional neural network.

PloS one May 7, 2025
Identifying relevant plant parts is one of the most significant tasks in the pharmaceutical industry. Correct identification minimizes the risk of mis-identification, which might have unfavorable effects, and it ensures that plants are used medicinal...
Neural Networks, Computer Plants, Medicinal Deep Learning Algorithms Convolutional Neural Networks Image Processing, Computer-Assisted Plant Leaves
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