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Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images
Published 2024-09-01“…Methods We combined computer vision algorithms with a convolutional network for fundus images and applied a faster region-based convolutional neural network (FRCNN) and artificial algae algorithm with support vector machine (AAASVM) classifiers. …”
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343
Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints
Published 2025-01-01“…We evaluate the proposed framework on two public databases (NIH Pancreas-CT and MICCAI Sliver07). …”
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344
MCTGNet: A Multi-Scale Convolution and Hybrid Attention Network for Robust Motor Imagery EEG Decoding
Published 2025-07-01Get full text
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345
Fishing operation type recognition based on multi-branch convolutional neural network using trajectory data
Published 2025-07-01“…To address this, this study proposes a novel framework integrating Geohash-based geocoding with embedding techniques inspired by natural language processing to extract spatiotemporal features from trajectory sequences. …”
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346
Seafloor Sediment Classification Using Small-Sample Multi-Beam Data Based on Convolutional Neural Networks
Published 2025-03-01“…To overcome the scarcity of seafloor sediment acoustic image data, we applied a deep convolutional generative adversarial network (DCGAN) for data augmentation, incorporating a de-normalization and anti-normalization module into the original DCGAN framework. …”
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347
A Focal Attention-Based Large Convolutional Kernel Network for Anomaly Detection of Coated Fuel Particles
Published 2025-05-01“…To address these issues, this study proposes an innovative focal attention-based large convolutional kernel network detection framework comprising three core modules. …”
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348
An Elliptic Kernel Unsupervised Autoencoder—Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing
Published 2025-01-01“…This article introduces the autoencoder graph ensemble model (AEGEM), a novel ensemble-based framework designed to enhance performance in both endmember extraction and abundance estimation. …”
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349
ACLC-Detection: A Network for Remote Sensing Image Detection Based on Attention Mechanism and Lightweight Convolution
Published 2025-07-01“…To address this issue, a novel detection framework named ACLC-Detection has been introduced. …”
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350
EHC-GCN: Efficient Hierarchical Co-Occurrence Graph Convolution Network for Skeleton-Based Action Recognition
Published 2025-02-01“…In this paper, we therefore propose an Efficient Hierarchical Co-occurrence Graph Convolution Network (EHC-GCN). By employing a simple and practical hierarchical co-occurrence framework to adjust the degree of feature aggregation on demand, we first use spatial graph convolution to learn the local features of joints and then aggregate the global features of all joints. …”
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351
Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network
Published 2019-01-01“…Moreover, through an in-depth study of the multicolumn convolutional neural network framework, this paper finds that the number of features and the convolution kernel size at different levels of the convolutional neural network are different. …”
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352
Residual capsule network with threshold convolution and attention mechanism for forest fire detection using UAV imagery
Published 2025-07-01“…This paper introduces ResCaps-TC-Attn-Fire, a novel deep learning framework tailored for UAV-based forest fire detection, combining Residual-Capsule Networks, Threshold Convolution, and Attention Mechanisms. …”
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353
LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection
Published 2025-05-01“…To address the above challenges, we propose a new target detection framework for complex remote sensing images, LS-MambaNet. …”
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354
A Novel Model for Predicting PM2.5 Concentrations Utilizing Graph Convolutional Networks and Transformer
Published 2025-01-01“…In response, this paper proposes a new approach based on Graph Convolutional Networks (GCN) and Transformer. To enhance the model’s predictive performance, we designed a new Transformer architecture named FFPformer, which incorporates the Fast Fourier Transform into the Transformer framework. …”
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355
Impact of the Radar Image Resolution of Military Objects on the Accuracy of their Classification by a Deep Convolutional Neural Network
Published 2022-02-01“…An eight-layer convolutional neural network was designed, trained and tested using the Keras library and Tensorflow 2.0 framework. …”
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356
WaViT-CDC: Wavelet Vision Transformer With Central Difference Convolutions for Spatial-Frequency Deepfake Detection
Published 2025-01-01“…To address these challenges, a novel end-to-end Wavelet Central Difference Convolutional Vision Transformer framework is designed to enhance spatial-frequency deepfake detection. …”
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357
Precision Recognition of Rock Thin Section Images With Multi‐Head Self‐Attention Convolutional Neural Networks
Published 2025-06-01“…We propose a lightweight framework that integrates the multi‐head self‐attention (MSA) mechanism into classical convolutional neural network (CNN) architectures, and is hereinafter denoted as MSA‐CNN. …”
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358
Translational approach for dementia subtype classification using convolutional neural network based on EEG connectome dynamics
Published 2025-05-01“…We also employed a convolutional neural network model, enhanced with these dynamic features, to differentiate between dementia subtypes. …”
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359
Melanoma Skin Cancer Recognition with a Convolutional Neural Network and Feature Dimensions Reduction with Aquila Optimizer
Published 2025-03-01“…<b>Conclusions:</b> The deep learning-Aquila Optimizer (DL-AO) framework offers a highly efficient and accurate approach for melanoma detection, making it suitable for deployment in resource-constrained environments such as mobile and edge computing platforms. …”
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360
Enhanced convolutional neural networks for defect detection in fiber-reinforced composites: a hyperparameter optimization approach
Published 2025-08-01“…This study presents an automated defect classification framework using convolutional neural networks (CNNs) designed to identify these five defect types from scanning electron microscopy (SEM) images. …”
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