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Retrieval of Passive Seismic Virtual Source Data Under Non-Ideal Illumination Conditions Based on Enhanced U-Net
Published 2025-05-01“…By integrating a feature fusion module into U-Net, multi-scale sampling information is leveraged to improve the network’s ability to capture detailed PVS data features. …”
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863
MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with Application in Colonic Polyp Image Segmentation
Published 2024-11-01“…Specifically, this study applied this method to the early detection of colonic polyps and to implement a model called MugenNet for colonic polyp image segmentation. We conducted a comprehensive experiment to compare MugenNet with other CNN models on five publicly available datasets. …”
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GLAI-Net: Global–Local Awareness Integrated Network for Semantic Change Detection in Remote Sensing Images
Published 2025-01-01“…Recently, multitask networks have become the main paradigm for SCD, but their detection performance is still affected by limited multi-scale feature extraction and insufficient cross-task information interaction. To address these issues, we propose a global–local awareness integrated network (GLAI-Net) for SCD in remote sensing images. …”
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866
PSR-LeafNet: A Deep Learning Framework for Identifying Medicinal Plant Leaves Using Support Vector Machines
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867
Corrections to “Pest Identification Based on Fusion of Self-Attention With ResNet”
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868
Modeling crystal defects using defect informed neural networks
Published 2025-07-01“…Here, we introduce Defect-Informed Equivariant Graph Neural Network (DefiNet), a model specifically designed to accurately capture defect-related interactions and geometric configurations in point-defect structures. …”
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869
TCI-Net: Structural Feature Enhancement and Multi-Level Constrained Network for Reliable Thin Crack Identification on Concrete Surfaces
Published 2025-01-01“…This study proposes a reliable crack identification method using the U-Net semantic segmentation network, incorporating image structural feature enhancement and multi-level consistency constraints. …”
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870
TongueNet: a multi-modal fusion and multi-label classification model for traditional Chinese Medicine tongue diagnosis
Published 2025-04-01“…TongueNet provides a new approach for the intelligent development of TCM tongue diagnosis.…”
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871
Performance Analysis of SpectralNet Algorithm on Fashion MNIST and KMNIST Datasets: A Study on Clustering Efficiency and Resource Utilization
Published 2025-06-01“…The research reveals how SpectralNet handles accuracy-efficiency relationships in dataset analysis to demonstrate its practical capabilities for complex information. …”
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Predicting Epileptic Seizures Using EfficientNet-B0 and SVMs: A Deep Learning Methodology for EEG Analysis
Published 2025-01-01“…This study proposes a novel framework combining a convolutional neural network (CNN) based on EfficientNet-B0 and an ensemble of six Support Vector Machines (SVMs) with a voting mechanism for robust seizure prediction. …”
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874
Capturing Subgrid Cold Pool Dynamics With U‐Net: Insights From Large‐Eddy Simulation for Storm‐Resolving Modeling
Published 2025-07-01“…Results show that the U‐Net models effectively capture cold pool characteristics, particularly their edges and intensity distribution at coarser scales. …”
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WIVIDOSA-Net: Wigner–Ville distribution based obstructive sleep apnea detection using single lead ECG signal
Published 2025-06-01“…Then, SWVSs were fed as input to our newly developed DLM named WIgner–VIlle Distribution-based Obstructive Sleep Apnea convolutional neural network (WIVIDOSA-Net) as well as other standard pretrained ResNet-18 and ResNet-50 for comparison. …”
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877
Enhancing Security in CPS Industry 5.0 using Lightweight MobileNetV3 with Adaptive Optimization Technique
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878
U-Net 3+ for anomalous diffusion analysis enhanced with mixture estimates (U-AnD-ME) in particle-tracking data
Published 2025-01-01“…Here, we introduce a novel machine-learning framework, U-net 3+ for anomalous diffusion analysis enhanced with mixture estimates (U-AnD-ME), that applies a U-Net 3+ based neural network alongside Gaussian mixture models to enable highly accurate characterisation of single-particle tracking data. …”
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Information about 12th International Congress on antiphospholipid antibodies
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