An ensemble-based 3D residual network for the classification of Alzheimer's disease. by Xiaoli Yang, Jiayi Zhou, Chenchen Wang, Xiao Li, Jiawen Wang, Angchao Duan, Nuan Du

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3D CAD model classification based on Convolutional Neural Network by DING Bo, YI Ming

“…Due to the intrinsic complexity of 3D CAD models, the automatic model classification methods are scarce. …”
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The International Classification of Headache Disorders: Anything New in 3rdEdition? by Sanjay Prakash

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Version [1.0.3] — [CACP: Classification Algorithms Comparison Pipeline] by Sylwester Czmil, Jacek Kluska, Anna Czmil

“…We present the first major release of the Classification Algorithms Comparison Pipeline (CACP). …”
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An Automated Wavelet Scattering Network Classification Using Three Stages of Cataract Disease by Enas Hamood Al-Saadi, Ahmed Nidhal Khdiar, Lamis Hamood Al-Saadi

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Evaluating the three-level approach of the U-smile method for imbalanced binary classification. by Barbara Więckowska, Katarzyna B Kubiak, Przemysław Guzik

“…Real-life binary classification problems often involve imbalanced datasets, where the majority class outnumbers the minority class. …”
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Classification of the stages of Alzheimer’s disease based on three-dimensional lightweight neural networks by Jun Li, Juntong Liu, Yang Su, Jie Chang, Mingquan Ye

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2D and 3D Classification Systems for Adolescent Idiopathic Scoliosis: Clinical Implications and Technological Advances by Wenqing Wei, Liang Cheng, Yating Dong, Tianyuan Zhang, Yaolong Deng, Jiale Gong, Fang Xie, Junlin Yang

Subjects: “…3D classification…”
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Novel 3-dimensional classification of cervical abrasion using CBCT: A comprehensive analysis by Tarun Kumar Singh, Ashish J. Johnson, Aakash Gupta, Ikroop Gill

Subjects: “…Classification…”
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T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification by Inigo Jauregi Unanue, Gholamreza Haffari, Massimo Piccardi

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Lens Opacities Classification System III-Based Computational Model of Nuclear Cataracts by Chi-Hung Lee, George C. Woo

“…To ensure alignment with the Lens Opacities Classification System III, colors were defined based on a color absorption coefficient limited within a predetermined range. …”
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SMCNet: State-Space Model for Enhanced Corruption Robustness in 3D Classification by Junhui Li, Bangju Huang, Lei Pan

“…Accurate classification of three-dimensional (3D) point clouds in real-world environments is often impeded by sensor noise, occlusions, and incomplete data. …”
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Impact of Dataset Size on 3D CNN Performance in Intracranial Hemorrhage Classification by Chun-Chao Huang, Hsin-Fan Chiang, Cheng-Chih Hsieh, Bo-Rui Zhu, Wen-Jie Wu, Jin-Siang Shaw

“…<b>Background:</b> This study aimed to evaluate the effect of sample size on the development of a three-dimensional convolutional neural network (3DCNN) model for predicting the binary classification of three types of intracranial hemorrhage (ICH): intraparenchymal, subarachnoid, and subdural (IPH, SAH, SDH, respectively). …”
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A phylogenetic classification of the Je language family [version 3; peer review: 2 approved, 3 approved with reservations] by Fabrício Ferraz Gerardi, Jonas Gregorio de Souza, Tim Wientzek, Fernando Orphão de Carvalho, Ivan Roksandic

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Modeling of milled straw heap separation in air-flow classificator with three pneumatic ducts by Yury I. Yermolyev, Artem A. Doroshenko, Sergey V. Belov

“…To this end, the mathematical expressions averaging the air classification indicators of the consistently functioning three pneumatic ducts and a stochastic quasistatic mathematical model of the separator operation with three pneumatic ducts in series are used. …”
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Sub-Pixel Displacement Measurement with Swin Transformer: A Three-Level Classification Approach by Yongxing Lin, Xiaoyan Xu, Zhixin Tie

“…The ST-SDM computes sub-pixel displacement values of different scales through three-level classification tasks, and solves the problem of positive and negative displacement with the rotation relative tag value method. …”
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Construction and Classification of Crystalline Topological Superconductor and Insulators in Three-Dimensional Interacting Fermion Systems by Jian-Hao Zhang, Shang-Qiang Ning, Yang Qi, Zheng-Cheng Gu

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Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM by ZHANG Jing, QI Guohong, CHEN Jingzhao, CAO Xiaoli, LI Lili

“…ObjectiveTo improve the classification accuracy of edible vegetable oils, an identification model based on three-dimensional fluorescence spectroscopy and ISSA-SVM was established.MethodsCombining the feature information of three-dimensional fluorescence spectroscopy, an improved sparrow search algorithm was used to optimize the parameters of the SVM model, constructing an edible vegetable oil identification method that integrates the characteristics of three-dimensional fluorescence spectroscopy information and the ISSA-SVM model.ResultsCompared with the SVM model, GA-SVM model, PSO-SVM model, and SSA-SVM model, the classification accuracy of the ISSA-SVM model for edible vegetable oils reached 100%.ConclusionThe ISSA-SVM model has higher convergence efficiency, system stability, and the ability to avoid local optimal solutions, which can effectively cope with complex and variable sample classification tasks.…”
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Three-Layer Retrieval and Self-Evaluation Classification Method Based on FastText Algorithm by Yidan Li, Huanhuan Hong, Luhong Wen

“…Our approach differs from conventional patent search processes. We have developed a three-level patent classification method that utilizes a multi-step search strategy with specific constraints, alongside an innovative classification system based on the FastText algorithm. …”
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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…In this paper, machine learning (ML) tools are deployed for detecting and classifying the faults in the connecting lines from 3-<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula> inverter output to the BLDC motor during operational mode in the EV platform, considering double-line and three-phase faults. …”
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