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Preprocessing

Beyond writing machines: A Kano model analysis of researchers’ hierarchical needs for AIGC services across the research lifecycle

Yong Kong, Tongqiang Dong, [ ... ], Ziyi Yang

Random subspace-based ensemble classifier for high-dimensional data Using SPARK

Venkaiah Chowdary Bhimineni, Rajiv Senapati

ESC-YOLOv8: An enhanced deep learning framework for semantic understanding of single-line diagram imagery

Hina Bhanbhro, Yew Kwang Hooi, [ ... ], Vengas Memon

Ensemble and temporal feature-based framework for rainfall classification in Bangladesh

Mahir Shahriar Tamim, Md. Samiul Alim, [ ... ], Md Musfique Anwar

Thermal imaging for sealing defect detection in pharmaceutical bags using a temporal fusion network

Liqiang Wang, Ziyang Leng, Cunmin Jiang, Rui Hua

Hybrid lightweight vision transformers with attention mechanism for feature extraction and classification of product designs

Abdul Wahid, Hikmat Ullah Khan, Anam Naz, Fawaz Khaled Alarfaj

Point cloud generation adversarial network based on self-attention and curvature

Fusheng Sun, Chaofan Shen, [ ... ], Fengguang Xiong

Interpretable machine learning for chronic kidney disease prediction: Insights from SHAP and LIME analyses

El Mehdi Chouit, Mohamed Rachdi, Mostafa Bellafkih, Brahim Raouyane

Bangla MedER: Multi-BERT ensemble approach for the recognition of Bangla medical entity

Tanjim Taharat Aurpa, Farzana Akter, [ ... ], Rubel Sheikh

Maximizing ball movement unpredictability in association football: A Rényi entropy-based approach to optimizing event distribution randomness

Ishara Bandara, Sergiy Shelyag, [ ... ], Maia Angelova

Efficient talent identification in women’s football: A ranking-based approach for goal scoring analysis

Songyi Song, Hee-Su Kim

Machine learning prediction of metabolic-associated fatty liver disease in type 2 diabetes: Emphasizing data imputation and feature selection

Zahra Khosravi, Farnaz Barzinpour, [ ... ], Alireza Esteghamati

Trustworthy AI for medical decisions: Adversarially robust and fair machine learning prediction for Parkinson’s disease

Junaid Muhammad, Mitra Ghergherehchi, [ ... ], Nasir Rahim

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