Estimation Model for Bread Quality Proficiency Using Fuzzy Weighted Relevance Vector Machine Classifier by Zainab N. Ali, Iman Askerzade, Saddam Abdulwahab

“…The processed data and the attributes are given as input to the classifier to obtain final estimation results. The efficient Fuzzy Weighted Relevance Vector Machine (FWRVM) classifier model is developed for this achieving this objective. …”
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An Ensemble Feature Selection Approach-Based Machine Learning Classifiers for Prediction of COVID-19 Disease by Md. Jakir Hossen, Thirumalaimuthu Thirumalaiappan Ramanathan, Abdullah Al Mamun

“…Different feature selection approaches including chi-square test, recursive feature elimination (RFE), genetic algorithm (GA), particle swarm optimization (PSO), and random forest are evaluated for their effectiveness in enhancing the classification accuracy of the machine learning classifiers. …”
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Convolutional neural networks for classifying healthy individuals practicing or not practicing meditation according to the EEG data by X. Fu, S. S. Tamozhnikov, A. E. Saprygin, N. A. Istomina, A. N. Klemeshova, A.  N. Savostyanov

“…The aim of our study was to develop, train and test a convolutional neural network capable of classifying individuals into groups of practitioners and non-practitioners of meditation by analysis of eventrelated brain potentials recorded during stop-signal paradigm. …”
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Rolling Bearing Fault Diagnostic Method Based on VMD-AR Model and Random Forest Classifier by Te Han, Dongxiang Jiang

“…Analysis results show that this method based on VMD-AR model can extract fault features accurately and RF classifier has been proved to outperform comparative classifiers.…”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The rapid expansion of devices on the Internet of Things (IoTs) has led to a significant rise in IoT botnet attacks, creating an urgent need for advanced detection and classification methods. This study aims to evaluate the effectiveness of Kolmogorov-Arnold Networks (KANs) and their architectural variations in classifying IoT botnet attacks, comparing their performance with traditional machine learning and deep learning models. …”
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Hybrid Learning Model for intrusion detection system: A combination of parametric and non-parametric classifiers by C. Rajathi, P. Rukmani

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Dynamic Classifier Auditing by Unsupervised Anomaly Detection Methods: An Application in Packaging Industry Predictive Maintenance by Fernando Mateo, Joan Vila-Francés, Emilio Soria-Olivas, Marcelino Martínez-Sober, Juan Gómez-Sanchis, Antonio José Serrano-López

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Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images by N.A. Firsov, V.V. Podlipnov, N.A. Ivliev, D.D. Ryskova, A.V. Pirogov, A.A. Muzyka, A.R. Makarov, V.E. Lobanov, V.I. Platonov, A.N. Babichev, V.A. Monastyrskiy, V.I. Olgarenko, D.P. Nikolaev, R.V. Skidanov, A.V. Nikonorov, N.L. Kazanskiy, V.A. Soyfer

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Classifications for Proliferative Vitreoretinopathy (PVR): An Analysis of Their Use in Publications over the Last 15 Years by Salvatore Di Lauro, Mustafa R. Kadhim, David G. Charteris, J. Carlos Pastor

“…To evaluate the current and suitable use of current proliferative vitreoretinopathy (PVR) classifications in clinical publications related to treatment. …”
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Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis by Zhigao Zeng, Zhiqiang Wen, Shengqiu Yi, Sanyou Zeng, Yanhui Zhu, Qiang Liu, Qi Tong

“…This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. …”
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Application of Improved Naive Bayesian-CNN Classification Algorithm in Sandstorm Prediction in Inner Mongolia by Li Tiancheng, Ren Qing-dao-er-ji, Qiu Ying

“…This paper proposed an efficient sandstorm prediction method that considered both the effect of atmospheric movement and ground factors on sandstorm occurrence, called improved naive Bayesian-CNN classification algorithm (INB-CNN classification algorithm). …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

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Lie Group Classification of a Generalized Lane-Emden Type System in Two Dimensions by Motlatsi Molati, Chaudry Masood Khalique

“…The classical approach of group classification is employed for classification. …”
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New MUSA classification of adenomyosis: correlation of symptoms and clinical severity with direct and indirect features by Sangam Jha, Nikita Prakash, Vikas C. Jha, Upasna Sinha

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Gene Selection Based Cancer Classification With Adaptive Optimization Using Deep Learning Architecture by Anju Das, N. Neelima, K. Deepa, Tolga Ozer

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Characterization and Classification of Modes in Acoustic Emission Based on Dispersion Features and Energy Distribution Analysis by M.A. Torres-Arredondo, C.-P. Fritzen

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Gene Structures, Classification, and Expression Models of the DREB Transcription Factor Subfamily in Populus trichocarpa by Yunlin Chen, Jingli Yang, Zhanchao Wang, Haizhen Zhang, Xuliang Mao, Chenghao Li

“…The phylogenic construction suggests that the PtrDREB gene subfamily can be classified broadly into six subtypes (DREB A-1 to A-6) in Populus. …”
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Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features by Aiga Andrijanova, Lasma Bugovecka, Sergejs Isajevs, Donats Erts, Uldis Malinovskis, Andis Liepins

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Deep Convolutional Network Based Machine Intelligence Model for Satellite Cloud Image Classification by Kalyan Kumar Jena, Sourav Kumar Bhoi, Soumya Ranjan Nayak, Ranjit Panigrahi, Akash Kumar Bhoi

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Fungicide Resistance Action Committee’s (FRAC) Classification Scheme of Fungicides According to Mode of Action by Frederick M. Fishel, Megan M. Dewdney

“…This revised guide addresses management of pesticide resistance and describes the Fungicide Resistance Action Committee’s (FRAC) classification of fungicides and bactericides registered for agricultural and non-agricultural use in Florida by their modes of action. …”
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