There has been growing attention to multi-class classification problems, particularly those challenges of imbalanced class distributions. To address these challenges, various strategies, including ...
Abstract: A multi-label image classification is a challenging task as it has to map an input image to a vector of outputs. This work presents a single and efficient model to perform multi-label and ...
Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets
Shahid SB, Kaikaus M, Kabir MH, Yousuf MA, Azad AKM, Al-Moisheer AS, Alotaibi N, Alyami SA, Bhuiyan T and Moni MA (2025) Novel deep learning for multi-class classification of Alzheimer’s in disability ...
WeatherClassifyNet is a machine learning project focused on the classification of weather conditions from images. This project uses a multi-class classification approach to identify different weather ...
Abstract: Aggregating information from multiple views is essential to accurately identifying similar objects. Nevertheless, existing datasets have limitations that hinder the development of practical ...
Only a few classification models aid multi-class classification. Specific algorithms, including logistic regression and perceptron, work best with binary classification and do not support more than ...
Transfer learning in machine learning models, particularly deep learning architectures, requires diverse datasets to ensure robustness and generalizability across tasks and domains. This repository ...
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