ALTERNATIVE SETTLEMENT SYSTEM IN THE FUEL AND ENERGY COMPLEX: CLASSIFICATION AND MAIN FEATURES by O. Baikova, D. Kulakov

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Management of Edentulous Microstomia Patient: A Case Report and Classification System by Maria S. Abbasi, Naseer Ahmed, Adil Bin Irfan, Samar Al-Saleh, Tariq Abduljabbar, Fahim Vohra

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Classification of jurisprudential issues according to Maliki jurists in the eighth century AH by عادل خذيري, عمر مونة

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About the confusion-matrix-based assessment of the results of imbalanced data classification by V. V. Starovoitov, Yu. I. Golub

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Facial biotype and maxillomandibular skeletal classification in Angolan patients with dentomaxillofacial anomalies by Yosvany Herrero Solano

“…<br /><strong>Results</strong>: 46.34% of patients presented maxillomandibular skeletal class II. …”
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Semi-Supervised Learning With Wafer-Specific Augmentations for Wafer Defect Classification by Uk Jo, Seoung Bum Kim

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Lateral Polydactyly of the Foot: Surgical Outcomes Based on a New Classification by Junko Otsuka, MD, Emiko Horii, MD, Shukuki Koh, MD, Hiroki Takeshige, MD

“…The objective of this study was to propose a novel classification for lateral polydactyly of the foot that integrates both visual appearance and radiographic findings and to delineate surgical techniques and their outcomes based on this classification. …”
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Step-by-step classification detection algorithm of SPPM based on K-means clustering by Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU

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Automatic Classification of Microseismic Signals Based on MFCC and GMM-HMM in Underground Mines by Pingan Peng, Zhengxiang He, Liguan Wang

“…The results show that our proposed method obtains an accuracy of 92.46%, which demonstrates the effectiveness of the method for automatic classification of microseismic data in underground mines.…”
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The Toulouse–Kleman homotopic classification of topological defects in ordered systems illustrated by experiments by Pieranski, Pawel, Godinho, Maria Helena

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Rule-Based Classification Based on Ant Colony Optimization: A Comprehensive Review by Sayed Kaes Maruf Hossain, Sajia Afrin Ema, Hansuk Sohn

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Performance Comparison of IoT Classification Models using Ensemble Stacking and Feature Importance by nabila putri setiawan, Adhitya Nugraha, Ardytha Luthfiarta, Yudha Mulyana

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Fourier or Wavelet bases as counterpart self-attention in spikformer for efficient visual classification by Qingyu Wang, Qingyu Wang, Duzhen Zhang, Xinyuan Cai, Tielin Zhang, Bo Xu

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Temporal integration of ResNet features with LSTM for enhanced skin lesion classification by Sasmita Padhy, Sachikanta Dash, Naween Kumar, Shailendra Pratap Singh, Gyanendra Kumar, Poonam Moral

“…The precise classification of skin lesions is essential for the early identification and efficient treatment of skin cancer. …”
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Relationship between Cognitive Learning Psychological Classification and Neural Network Design Elements by Xing Yang, Tingjun Yong, Meihua Li, Wenying Wang, Huichun Xie, Jinping Du

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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

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Vegetation Classification in a Mountain–Plain Transition Zone in the Sichuan Basin, China by Wenqian Bai, Zhengwei He, Yan Tan, Guy M. Robinson, Tingyu Zhang, Xueman Wang, Li He, Linlong Li, Shuang Wu

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Skin Lesion Classification Through Test Time Augmentation and Explainable Artificial Intelligence by Loris Cino, Cosimo Distante, Alessandro Martella, Pier Luigi Mazzeo

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Liver fibrosis stage classification in stacked microvascular images based on deep learning by Daisuke Miura, Hiromi Suenaga, Rino Hiwatashi, Shingo Mabu

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A class imbalance aware hybrid model for accurate rice variety classification by Hanumesh Vaidya, K.V. Prasad, C. Rajashekhar, D Tripathi, Renuka S, Jyoti Shetty, Kumar Swamy, Shobha Y

“…The results of our comprehensive evaluation are compelling, with the XGB-MLP model achieving outstanding accuracy across various classification tasks: 99.86 % for binary class, 99.95 % for multi-class, and 98.46 % for a challenging multi-class scenario using a merged dataset. …”
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