Retraction Notice: Brain Tumors Classification System Using Convolutional Recurrent Neural Network by Akila V., Abhilash P.K., Satya Phanindra P Bala Venakata, Kumar J Pavan, Kavitha A.

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The analysis of sculpture image classification in utilization of 3D reconstruction under K-means++ by Xuhui Wang

“…Abstract This study aims to address the issues of accuracy and efficiency in sculpture image classification. …”
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A multi-label classification method for disposing incomplete labeled data and label relevance by Lina ZHANG, Lingpeng DAI, Tai KUANG

“…Multi-label classification methods have been applied in many real-world fields，in which the labels may have strong relevance and some of them even are incomplete or missing.However，existing multi-label classification algorithms are unable to handle both issues simultaneously.A new probabilistic model that can automatically learn and exploit multi-label relevance was proposed on label relevance and missing label classification simultaneously.By integrating out the missing information，it also provides a disciplined approach to handle missing labels.Experiments on a number of real world data sets with both complete and incomplete labels demonstrated that the proposed method can achieve higher classification and prediction evaluation scores than the existing multi-label classification algorithms.…”
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Towards a Functional Socio-Legal Classification of the Legal Norms for the Regulatory Effectiveness Analysis by Félix Arias-Schreiber, Antonio Peña Jumpa

“…In the end of the work we present an alternative classification.…”
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Improving kernel ridge regression for medical data classification based on meta-heuristic algorithms

“…Of the three datasets, it achieved an overall result of 79 % in producing the highest classification accuracy. © 2025 The Authors…”
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The Classification of Metastatic Spine Cancer and Spinal Compression Fractures by Using CNN and SVM Techniques by Woosik Jeong, Chang-Heon Baek, Dong-Yeong Lee, Sang-Youn Song, Jae-Boem Na, Mohamad Soleh Hidayat, Geonwoo Kim, Dong-Hee Kim

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Cryptocurrencies and Digital Assets in the Modern Legal and Financial System of Russia: Problems of Terminology and Classification by A. V. Krupochkin, I. P. Khominich

“…The article is devoted to the problem of terminological uncertainty and the lack of a unified classification of cryptocurrencies and digital assets in modern Russian legislation. …”
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Classification of lung cancer severity using gene expression data based on deep learning by Ali Bou Nassif, Nour Ayman Abujabal, Aya Alchikh Omar

“…As a result, the optimized CNN model using F-test feature selection method, achieved high classification accuracies of approximately 93.94% for LUAD and 88.42% for LUSC.…”
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Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System by Woncheol Park, Seungmin Oh, Seonghyun Park

“…The system addresses the challenge of understanding internal issues that may be difficult to express in traditional face-to-face counseling. …”
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LED array-based multi-angle light scattering for aspirating smoke detection and classification by Soocheol Kim, Hoesung Yang, Kwangsoo Cho, Kyuwon Han, Yusun Ahn, Jin Hwa Ryu, Kangbok Lee

“…The feasibility of smoke detection and classification was verified by evaluating the classification performance of 10 types of fire and non-fire aerosols using general supervised learning algorithms. …”
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Analysis of Fault Detection and Classification in Photovoltaic Arrays Using Neural Network-Based Methods by Arizadayana Zahalan, Samila Mat Zali, Ernie Che Mid, Noor Fazliana Fadzail

“…This study addresses these issues by exploring fault detection and classification in PV arrays using neural network (NN) -based techniques. …”
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Segmentation and Classification of Skin Cancer Diseases Based on Deep Learning: Challenges and Future Directions by Abdulrahman Dira Khalaf, Hazlina Hamdan, Alfian Abdul Halin, Noridayu Manshor

“…This study also examines the critical challenges of deploying DL models in clinical practice, covering issues including dataset diversity, model interpretability, and real-world implementation feasibility. …”
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Classification of Beef, Goat, and Pork using GLCM Texture-Based Backpropagation Neural Network by Irma Saraswati, Rian Fahrizal, Anugrah Nuur Fauzan, Muchtar Ali Setyo Yudono

“…The findings of this study suggest that GLCM is an effective tool for deriving relevant statistical parameters necessary for classification. This research makes a significant contribution to developing a meat identification system that safeguards consumers and promotes awareness of food safety issues. …”
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Deep Metric Learning for Fine-Grained Ship Classification in SAR Images with Sidelobe Interference by Haibin Zhu, Yaxin Mu, Wupeng Xie, Kang Xing, Bin Tan, Yashi Zhou, Zhongde Yu, Zhiying Cui, Chuang Zhang, Xin Liu, Zhenghuan Xia

“…To address the aforementioned issues, a novel classification framework for sidelobe-affected SAR imagery is proposed. …”
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ECGNet: High-Precision ECG Classification Using Deep Learning and Advanced Activation Functions by Muhammad Abubakar, Ahsan Raza, Arfan Ali Nagra, Anas Bilal, Ahmad Alshammari, Monir Abdullah, Sahraoui Dhelim

“…Additionally, the Modified SparseMax classifier is employed to enhance the classification by mapping logits to sparse probability distributions. …”
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Comparative Assessment of Several Effective Machine Learning Classification Methods for Maternal Health Risk by Md Nurul Raihen, Sultana Akter

“…Early identification and classification of risk variables can successfully prevent pregnancy-related issues by reducing the number of errors. …”
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Utilization of FTIR Spectroscopic Method in Classification and Analysis of Mineral Samples Containing Sodium and Potassium by Adnan Kenar, Fahriye Öğüt

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Enhancing malaria detection and classification using convolutional neural networks-vision transformer architecture by Emmanuel Ahishakiye, Fredrick Kanobe, Danison Taremwa, Bartha Alexandra Nantongo, Leonard Nkalubo, Shallon Ahimbisibwe

“…More so, existing machine learning models used in malaria detection and classification have low performance and overfitting issues. …”
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Orga-Dete: An Improved Lightweight Deep Learning Model for Lung Organoid Detection and Classification by Xuan Huang, Qin Gao, Hanwen Zhang, Fuhong Min, Dong Li, Gangyin Luo

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Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification by Yasin Kaya, Ezgisu Akat, Serdar Yıldırım

“…However, the manual classification of brain tumors is a laborious and complex task. …”
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