This is the code for SGIR, a semi-supervised framework for Graph Imbalanced Regression. Data imbalance is easily found in annotated data when the observations of certain continuous label values are ...
Abstract: Due to the rapid development of deep learning techniques, no-reference image quality assessment (NR-IQA) has achieved significant improvement. NR-IQA aims to predict a real-valued variable ...
Abstract: The performance of medical image classification has been enhanced by deep convolutional neural networks (CNNs), which are typically trained with cross-entropy (CE) loss. However, when the ...
Accurate predictions of earthquakes are crucial for disaster preparedness and risk mitigation. Conventional machine learning models like Random Forest, SVR, and XGBoost are frequently used for seismic ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
1 Centre for Polymer Science and Technology, Department of Chemistry, University of Calicut, Tenhipalam, Kerala, India 2 Department of Chemistry, M.P.M.M.S.N. Trusts College, Palakkad, Kerala, India ...
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