Hybrid Method for Point Cloud Classification by Abdurrahman Hazer, Remzi Yildirim

Subjects: “…Point cloud classification…”
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Machine Learning Classification of 3D Intracellular Trafficking Using Custom and Imaris-Derived Motion Features by Oleg Kovtun

“…Although considerable progress has been made, accurately distinguishing between different types of diffusion in three dimensions remains a significant challenge. …”
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Network analysis of headache diagnoses using international classification of headache disorders, 3rd edition by Pengfei Zhang, Thomas Berk, Thomas Berk

“…Background and objectiveThe International Classification of Headache Disorders, Third Edition (ICHD-3), significantly influences clinicians’ understanding of headache disorders. …”
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Classification of 3D CAD Models considering the Knowledge Recognition Algorithm of Convolutional Neural Network by Weiwei Wang, Dandan Sun

“…In order to improve the classification effect of the 3D CAD model, this paper combines the knowledge recognition algorithm of convolutional neural network to construct the 3D CAD model classification model. …”
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Research on Food Image Classification Algorithm based on Improved MobileNetV3-Large by HE Wei-chan, YANG Zhi-jing, QIN Jing-hui

“…In order to address these issues, this paper proposed a food image classification algorithm based on improved MobileNetV3-Large. …”
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T3SSLNet: Triple-Method Self-Supervised Learning for Enhanced Brain Tumor Classification in MRI by Md. Nasif Safwan, Souhardo Rahman, Mahamodul Hasan Mahadi, Md Iftekharul Mobin, Taharat Muhammad Jabir, Zeyar Aung, M. F. Mridha

“…In this study, we explored the use of self-supervised learning techniques to improve the classification performance for brain tumors. Specifically, we tested three SSL approaches SimCLR, MoCo, and BYOL, with ResNet-50 as the backbone architecture on a newly constructed dataset created by combining five public datasets. …”
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An effective flowchart for multimodal brain tumor binary classification with ranked 3D texture features by Mücahid Barstuğan

Subjects: “…3D feature extraction…”
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Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features by Tuan Le Dinh, Seungeun Lee, Hyemin Park, Sungwon Lee, Hyeondeok Choi, Keum San Chun, Joon-Yong Jung

“…In this study, we propose a hybrid approach that integrates deep learning and radiomics for chondroid tumor classification. First, we performed tumor segmentation using the nnUNetv2 framework, which provided three-dimensional (3D) delineation of tumor regions of interest (ROIs). …”
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LoDCalculator: A level of detail classification software for 3D models in the Blender environment by Bruno Rodriguez-Garcia, Ines Miguel-Alonso, Henar Guillen-Sanz, Andres Bustillo

Subjects: “…3D modelling…”
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Research advances in maxillofacial characteristics, classification and treatment of facial asymmetry with skeletal Class Ⅲ malocclusion by ZHANG Linlin, LIU Dongxu

“…This article aims to review recent progress of research on the maxillofacial features, classification, and treatment of skeletal Class Ⅲ malocclusion with facial asymmetry, in order to provide reference for clinical diagnosis and treatment.…”
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Lip-Reading Classification of Turkish Digits Using Ensemble Learning Architecture Based on 3DCNN by Ali Erbey, Necaattin Barışçı

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Hierarchical 2-D/3-D Object-Based Classification of Photogrammetric Textured Mesh Models by Zhongwen Hu, Jinhua Zhang, Zhigang Liu, Yinghui Zhang, Jingzhe Wang, Qian Zhang, Guofeng Wu

“…To address this issue, we propose a hierarchical object-based method for the classification of TMMs, consisting of three key steps: 1) the TMM is first hierarchically segmented into ground surface meshes and off-ground 3-D objects using a cloth-simulated filtering algorithm; 2) the ground surface mesh is projected to 2-D ortho-image, where object-based image classification is used to classify pixels. …”
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KDDC: a new framework that integrates kmers, dataset filtering, dimension reduction and classification algorithms to achieve immune cell heterogeneity classification by Nan Zhang, Nan Zhang, Shishun Zhao, Runze Wu, Xizi Luo, Ming Yang, Zecheng Chang, Jianting Xu

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3D‐TabNetHS: A hyperspectral image classification method based on improved interpretable 3D attentive TabNet by Ning Li, Daozhi Wei, Shucai Huang, Yong Zhang

“…Therefore, this paper proposes classification methods based on improved attention interpretable table learning (TabNet) named 3D TabNet HSI (3D‐TabNetHS) and unsupervised 3D TabNet HSI (U3D‐TabNetHS). …”
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Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification by R. Rajesh Sharma, P. Marikkannu

“…The primary objective of this work is to propose a three-dimensional (3D) novel brain tumor classification model using MRI images with both micro- and macroscale textures designed to differentiate the MRI of brain under two classes of lesion, benign and malignant. …”
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Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model by Qunjia Zhang, Zhenhua Guo, Lei Liu, Jiacheng Mei, Le Wang

“…Band ratios were formulated based on the spectral characteristics. The 3D spectral feature space was constructed using these derived features to establish classification rules. …”
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Classification of Common Bean Landraces of Three Species Using a Neuroevolutionary Approach with Probabilistic Color Characterization by José-Luis Morales-Reyes, Elia-Nora Aquino-Bolaños, Héctor-Gabriel Acosta-Mesa, Nancy Pérez-Castro, José-Luis Chavez-Servia

“…In this work, we propose a methodology for classifying bean landrace samples using three two-dimensional histograms with data in the CIE L*a*b* color space while additionally integrating chroma (C*) and hue (h°) to develop a new proposal from histograms, employing deep learning for the classification task. …”
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Phenomenological classification of cultural heritage: role of virtual reality by Hyuk-Jin Lee

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Evaluation of the precision and accuracy in the classification of breast histopathology images using the MobileNetV3 model by Kenneth DeVoe, Gary Takahashi, Ebrahim Tarshizi, Allan Sacker

“…Computer vision models have been proposed to assist human pathologists in classification tasks such as these. Using MobileNetV3, a convolutional architecture designed to achieve high accuracy with a compact parameter footprint, we attempted to classify breast cancer images in the BreakHis_v1 breast pathology dataset to determine the performance of this model out-of-the-box. …”
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MSA-Net: multiple self-attention mechanism for 3D lung nodule classification in CT images by Jiating Pan, Lishi Liang, Peng Sun, Yongbo Liang, Jianming Zhu, Zhencheng Chen

“…We introduced a streamlined 3D model structure to solve the problems of 2D models cannot extract spatial information effectively and 3D models have high complexity and large occupation of computing resources. …”
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