Biomedical data analysis has evolved rapidly from convolutional neural network-based systems toward transformer architectures and large-scale foundation ...
Abstract: Conventional Convolutional Neural Networks (CNNs) in the real domain have been widely used for audio classification. However, CNNs have limited ability to capture correlations across ...
ABSTRACT: This study presents a comparative analysis of two distinct machine learning approaches for multilingual text identification: character-level neural networks (CNN/RNN) and traditional Naive ...
In this tutorial, we take a hands-on approach to building an advanced convolutional neural network for DNA sequence classification. We focus on simulating real biological tasks, such as promoter ...
ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, particularly for planning treatment strategies in patients with maxillary transverse deficiency (MTD). Although ...
Abstract: The graph neural network (GNN) exhibits noteworthy performance in hyperspectral image classification (HSIC) due to its efficient message-passing structure, which employs the multilayer ...
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