EFFICIENCY ASSESSMENT OF EUCLIDEAN AND MAKHALANOBIS DISTANCES FOR SOLVING A MAJOR TEXT CLASSIFICATION PROBLEM by Anna V. Glazkova

“…Moreover, there has been little coverage of this issue in the works of Russian researchers. Method A comparison of the relative efficiencies of using Euclid and Mahalanobis distances was carried out within the framework of the implementation of an intelligent system for text automatic classification based on the age category of their recipients. …”
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Using Masked Image Modelling Transformer Architecture for Laparoscopic Surgical Tool Classification and Localization by Hisham ElMoaqet, Rami Janini, Mutaz Ryalat, Ghaith Al-Refai, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Thomas Neumuth, Knut Moeller, Nassir Navab

“…Furthermore, the model incorporates class weights to address the class imbalance issue resulting from different usage frequencies of surgical tools in surgeries. …”
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Infrared Image Classification and Detection Algorithm for Power Equipment Based on Improved YOLOv10 by Xiu Ji, Zheyu Yue, Hongliu Yang, Zehong Zhang

“…To address this problem, this paper proposes an infrared image classification and detection algorithm for power equipment based on the improved YOLOv10, named YOLOv10plus. …”
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Plant Disease Detection and Classification Using Deep Learning Methods: A Comparison Study by Pei-Wern Chin, Kok-Why Ng, Naveen Palanichamy

“…The presence issue of inaccurate plant disease detection persists under real field conditions and most deep learning (DL) techniques still struggle to achieve real-time performance. …”
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GPPK4PCM: pest classification model integrating growth period prior knowledge by Jianhua Zheng, Junde Lu, Yusha Fu, Ruolin Zhao, Jinfang Liu, Zhaoxi Luo, Zhijie Luo

“…To address this issue, we propose a Pest Classification Model Integrating Growth Period Prior Knowledge. …”
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Knowledge distillation with resampling for imbalanced data classification: Enhancing predictive performance and explainability stability by Kazuki Fujiwara

“…Machine learning classification models often struggle with imbalanced datasets, leading to poor performance in minority classes. …”
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Detection and classification of breast cancer in mammographic images with fine-tuned convolutional neural networks by Huong Hoang Luong, Hai Thanh Nguyen, Nguyen Thai-Nghe

“…Breast cancer is cancer that forms in the cells of the breasts and is a severe health issue that affects many people around the world, especially since it is the most deadly cancer in women. …”
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Dynamic Impact-Based Heavy Rainfall Warning with Multi-classification Machine Learning Approaches by Anand Shankar

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An improved SMOTE algorithm for enhanced imbalanced data classification by expanding sample generation space by Ying Li, Yali Yang, Peihua Song, Lian Duan, Rui Ren

“…Abstract Class imbalance in datasets often degrades the performance of classification models. Although the Synthetic Minority Over-sampling Technique (SMOTE) and its variants alleviate this issue by generating synthetic samples, they frequently overlook local density and distribution characteristics. …”
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

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Diabetic Retinopathy Classification With Deep Learning via Fundus Images: A Short Survey by Shanshan Zhu, Changchun Xiong, Qingshan Zhong, Yudong Yao

“…CNN models of ResNet and VGGNet with layers of tens or even hundreds are the most popular frameworks used for DR classification. The APTOS 2019 and EyePACS are the most widely used datasets for DR classification. …”
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On the Classification of Regions of the Russian Federation by Level of Socio-Economic Development and Innovation Activity Index by A. S. Vtorygin

“…The results of the study determine the effectiveness of the author’s approach to the issue of typologization of regions, and emphasize the visibility and interactivity of the tools used within the framework of the model. …”
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Learning Class-Aware Local Representations for Few-Shot Remote Sensing Scene Classification by Liu Wang, Li Zhuo, Hui Zhang, Jiafeng Li

“…Few-Shot Remote Sensing Scene Classification (FSRSSC) aims at recognizing novel categories with only a few labeled samples. …”
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Improved UWB-based indoor positioning system via NLOS classification and error mitigation by Shoude Wang, Nur Syazreen Ahmad

“…On the public dataset, the SVM-RFE algorithm achieved classification accuracies of 97.6% in the hallway environment and 96.6% in the office environment, outperforming transfer learning (TL) deep neural networks (DNNs) tested on the same dataset. …”
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Dual-Branch Multi-Dimensional Attention Mechanism for Joint Facial Expression Detection and Classification by Cheng Peng, Bohao Li, Kun Zou, Bowen Zhang, Genan Dai, Ah Chung Tsoi

“…This paper addresses the central issue arising from the (SDAC) of facial expressions, namely, to balance the competing demands of good global features for detection, and fine features for good facial expression classifications by replacing the feature extraction part of the “neck” network in the feature pyramid network in the You Only Look Once X (YOLOX) framework with a novel architecture involving three attention mechanisms—batch, channel, and neighborhood—which respectively explores the three input dimensions—batch, channel, and spatial. …”
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VR Vertigo Level Classification Using a Multi-Dimensional Taylor Network Approach by Ziyan Wang, Ying Yan, Jun Cai, Chengcheng Hua, Na Liu, Qi Chen, Ming Li, Danxu Zhang

“…However, traditional MTN models are primarily used for prediction tasks and are not suitable for classification. To address this issue, this paper proposes a Backpropagation Multivariate Taylor Network (BP-MTN) classifier for diagnosing VR vertigo levels. …”
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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…The result shows that the model precision can reach 99.71%, and Yuluxiang’s recognition and classification precision increased from 96.4% to 98.3%. …”
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Double weighted k nearest neighbours for binary classification of high dimensional genomic data by Amjad Ali, Zardad Khan, Hailiang Du, Saeed Aldahmani

“…The high dimensional nature of this type of data, characterized by a large number of gene features substantially exceeding its sample size, makes it challenging for existing methods to work efficiently in terms of prediction accuracy and execution time. To address this issue, a new classification procedure called double weighted k nearest neighbours ( $$\hbox {DW}k\hbox {NN}$$ ) is proposed. …”
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An Efficient Topology Construction Scheme Designed for Graph Neural Networks in Hyperspectral Image Classification by Yu Zhang, Xin Li, Yaoqun Xu

“…In particular, by combining these models with our method, the classification performance was significantly improved. …”
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Synthetic Data-Driven Approaches for Chinese Medical Abstract Sentence Classification: Computational Study by Jiajia Li, Zikai Wang, Longxuan Yu, Hui Liu, Haitao Song

“…However, Chinese medical abstract classification research is hindered by a lack of suitable datasets. …”
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