Crop Classification and Yield Prediction Using Robust Machine Learning Models for Agricultural Sustainability by Abid Badshah, Basem Yousef Alkazemi, Fakhrud Din, Kamal Z. Zamli, Muhammad Haris

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Progress of fracture mapping technology based on CT three-dimensional reconstruction by Jichao Liu, Ziyan Zhang, Ji Qu, Chengdong Piao

“…This technology visually representing the morphology of fractures by overlaying fracture lines from multiple fracture models onto a standard model through three-dimensional reconstruction. …”
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Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification by Yasin Kaya, Ezgisu Akat, Serdar Yıldırım

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Outlier detection in ground-measured solar resource data using statistical classification models by Chantelle Clohessy, Warren Brettenny, Waldo Abrahams

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A stacking ensemble classification model for determining the state of nitrogen-filled car tires by Shah Viraj Chetan, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Sreelatha Anoop Prabhakaranpillai, Radha Manju Bhaskarapanicker

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Multi-model deep learning approach for the classification of kidney diseases using medical images by Waleed Obaid, Abir Hussain, Tamer Rabie, Dhafar Hamed Abd, Wathiq Mansoor

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An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques by Fariha Haque, Mohammad Asif Hasan, Md. Abu Ismail Siddique, Tonmoy Roy, Tonmoy Kanti Shaha, Yamina Islam, Avijit Paul, Muhammad E. H. Chowdhury

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Wheat Powdery Mildew Severity Classification Based on an Improved ResNet34 Model by Meilin Li, Yufeng Guo, Wei Guo, Hongbo Qiao, Lei Shi, Yang Liu, Guang Zheng, Hui Zhang, Qiang Wang

“…In this study, we present QY-SE-MResNet34, a deep learning-based classification model that builds upon ResNet34 to perform multi-class classification of wheat leaf images and assess powdery mildew severity at the single-leaf level. …”
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Models for analysis of water suitability by L. Makarchuk, T. Likhouzova

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Prognostic Value of a Classification and Regression Tree Model in Patients with Open-Globe Injuries by Danica T. Esteban, MD, Karlo Marco D. Claudio, MD, Cheryl A. Arcinue, MD

“…Objective: To evaluate the accuracy of the Classification and Regression Tree (CART) model in prognosticating visual outcomes of patients with open-globe injuries Methods: This was a retrospective, single-center, cohort study of patients with open-globe injuries seen over a two-year period. …”
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Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making by Yuuki Uchida, Yuuki Uchida, Takatoshi Hikida, Manabu Honda, Yuichi Yamashita

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Determining The Effect of Some Mechanical Properties on Color Maturity of Tomato With K-Star, Random Forest and Decision Tree (C4.5) Classification Algorithms by Hande Küçükönder, Kubilay Kazım Vursavuş, Fatih Üçkardeş

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RF-Based Sensing and AI Decision Support for Stroke Patient Monitoring: A Digital Twin Approach by Sagheer Khan, Usman Anwar, Aftab Khan, Tughrul Arslan

“…The Fine KNN algorithm provides the 93.4% and 92.3% classification accuracies of binary and multi-class classification respectively. …”
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Corrigendum on: Enhancing heart disease prediction accuracy by comparing classification models employing varied feature selection techniques [Serb. Jour. of Elect. Eng., Vol. 21, N... by Editorial

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An emotional classification method of Chinese short comment text based on ELECTRA by Shunxiang Zhang, Hongbin Yu, Guangli Zhu

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Classification system from Optical Coherence Tomography using transfer learning by Muhamad Asvial, Tobias Ivandito Margogo Silalahi, Muh. Asnoer Laagu

“…This research aims to create a decision support system to identify retinal diseases using a four-class classification problem. …”
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An Integrated Entropy–MAIRCA Approach for Multi-Dimensional Strategic Classification of Agricultural Development in East Africa by Chia-Nan Wang, Duy-Oanh Tran Thi, Nhat-Luong Nhieu, Ming-Hsien Hsueh

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CONCEPTUAL BASIS FOR THE CLASSIFICATION OF CREATIVE INDUSTRIES AND EMPIRICAL ANALYSIS OF THEIR DEVELOPMENT BASED ON TURNOVER DYNAMICS by Iryna Svyshchuk

“…The article provides a critical review of international classification approaches (DCMS, WIPO, UNESCO, UNCTAD) and proposes an author's classification model based on three parameters: the method of economic value creation, the form of the final product, and the type of interaction with the consumer. …”
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A fuzzy-optimized multi-level random forest (FOMRF) model for the classification of the impact of technostress by Gabriel James, Ifeoma, David, John, Samuel, Enefiok, Imeh Umoren, Ubong Etuk, Aloysius, Anietie, Saviour, Chikodili

“…Traditional machine learning models often struggle with the complexity and non-linearity of technostress classification. …”
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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…Using demographic, clinical and laboratory data of the patients, six different machine learning algorithms (SVM, KNN, ANN, Decision Tree, Naive Bayes and Discriminant Analysis) were used for classification. …”
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