Abstract: This study proposes an image-text multimodal classification algorithm based on a combination of convolutional neural networks (CNN) and Transformer, aiming to solve the key problems in ...
Abstract: Due to the explosive growth of digital content, automated text summary generation has become a critical task for digesting large amounts of information efficiently. In this work, we propose ...
Results: In the training set, LightGBM, XGBoost, and RF demonstrated the best performance among all models, with ROC-AUCs of 0.9977, 0.9311, and 0.9847, respectively. These models exhibited minimal ...
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