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Fine-Grained Building Classification in Rural Areas Based on GF-7 Data
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Cyclic Learning Rate-Based Co-Training for Image Classification With Noisy Labels
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Impact of Dataset Size on 3D CNN Performance in Intracranial Hemorrhage Classification
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Vegetation Classification in a Mountain–Plain Transition Zone in the Sichuan Basin, China
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Skin Lesion Classification Through Test Time Augmentation and Explainable Artificial Intelligence
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Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS
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127
Multiple-Wearable-Sensor-Based Gait Classification and Analysis in Patients with Neurological Disorders
Published 2018-10-01“…The placement-based classification of the shank sensor achieved 89.13% testing accuracy with the Decision Tree (DT) classifier algorithm. …”
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Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
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Classification of Cigarette Types Using Computer Vision: An Analysis of Smoke Aggregation Features
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A dataset of Antarctic ecosystems in ice-free lands: classification, descriptions, and maps
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Motor Imagery EEG Classification Based on Multi-Domain Feature Rotation and Stacking Ensemble
Published 2025-01-01“…Finally, we employ a stacking ensemble approach, where the prediction results of base classifiers corresponding to different domain features and the set of significant features undergo linear discriminant analysis for dimensionality reduction, yielding discriminative feature integration as input for the meta-classifier for classification. Results: The proposed method achieves average classification accuracies of 92.92%, 89.13%, and 86.26% on the BCI Competition III Dataset IVa, BCI Competition IV Dataset I, and BCI Competition IV Dataset 2a, respectively. …”
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Imaging Features of the Mesenchymal Tumors of the Breast according to WHO Classification: A Pictorial Essay
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Tracking algorithm of Siamese network based on online target classification and adaptive template update
Published 2021-08-01“…Aiming at the problem that tracking algorithm of Siamese network learned the embedded features of the tracked target and the object in the offline training stage, and these embedded features often lacked the target-specific context information, which made these tracking algorithms less robust, a tracking algorithm of the Siamese network based on online target classification and adaptive template update was proposed, which used SiamRPN++ as the baseline algorithm.Firstly, a cross-correlation feature map supervision module for classification was designed in the offline training phase to learn more discriminative embedded features.Secondly, an online target classification module that included an attention mechanism in the online tracking phase was designed, and the online update filter strategy in the module was used to filter out the background noise.Finally, an adaptive template update module was designed to update the target template information using the UpdateNet.The results of experiments on VOT2018 and VOT2019 datasets verify the effectiveness of the proposed algorithm, which brings 13.5% and 18.2% (EAO) improvement respectively compared with the baseline algorithm SiamRPN++.…”
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Research of the Method of Gear Fault Classification based on Contourlet Transform and Local Binary Pattern
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