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Motion Classification With Embroidery Bend Sensors Using Multiple Zigzag-Stitch for Loose-Fitting Garments
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Predictive value of myositis antibodies: role of semiquantitative classification and positivity for more than one autoantibody
Published 2025-01-01“…The PPV for malignancy was highest for anti-TIF1-γ (38%), followed by anti-PL-7 (32%). Stronger antibody band intensity was associated with higher PPVs for myositis and CTD but not for ILD or malignancies. …”
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Classification of palm oil fruit ripeness based on AlexNet deep Convolutional Neural Network
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Postoperative symptom changes following uterine artery embolization for uterine fibroid based on FIGO classification
Published 2025-01-01“…Abstract Background Classifying uterine fibroid using the International Federation of Gynecology and Obstetrics (FIGO) classification system assists treatment decision-making and planning. …”
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Feasibility of the International Caries Classification and Management System (ICCMS) Protocol in a Hospital-Based Setting in India
Published 2024-11-01“…Objective: To evaluate the feasibility of the International Caries Classification and Management System (ICCMS) protocol in a hospital-based setting in India. …”
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Automated orthodontic diagnosis via self-supervised learning and multi-attribute classification using lateral cephalograms
Published 2025-02-01“…Additionally, a multi-attribute classification network is proposed, leveraging attribute correlations to optimize parameters and enhance classification performance. …”
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ECGConVT: A Hybrid CNN and Vision Transformer Model for Enhanced 12-Lead ECG Images Classification
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Integrating deformable CNN and attention mechanism into multi-scale graph neural network for few-shot image classification
Published 2025-01-01“…Compared with the benchmark model, the classification accuracy has increased by 1.07% and 1.33% respectively; In the 5-way 5-shot task, the classification accuracy of the mini-ImageNet dataset was improved by 11.41%, 7.42%, and 5.38% compared to GNN, TPN, and dynamic models, respectively. …”
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Remote Sensing Scene Classification using ConvNeXt-Tiny Model with Attention Mechanism and Label Smoothing
Published 2024-06-01“…The experiments in this study also aim to prove that the integration of the attention module and LSR into the basic CNN network can improve precision, because the attention module can strengthen important features and weaken features that are less useful for classification. The experimental results proved that the integration of ECANet and LSR in the ConvNeXt-Tiny base network obtained a higher precision of 0.38% in the UC-Merced dataset, 0.7% in the AID, and 0.4% in the WHU-RS19 dataset than the ConvNeXt-Tiny model without ECANet and LSR. …”
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