This study uses a hybrid deep learning technique to classify asphalt, pavement, and unpaved roads. In real-world circumstances, image data noise can damage image categorization algorithms. This issue ...

Community websites bring many conveniences to people, and the classification of community content is playing an important role in website management and information searching. As the carrier of ...

This investigation, focusing on classification performance, compares the classic BERT and several hybrid versions (i.e., employing different training strategies and approximate Support Vector Machines ...

This paper investigates the application of Convolutional Neural Networks (CNNs) in MNIST handwritten digit recognition, with a particular focus on optimizing the ResNet-18 model. By introducing ...

Real-world data usually exhibits a long-tailed distribution, with a few frequent labels and a lot of few-shot labels. The study of institution name normalization is a perfect application case showing ...

The growing volume of unstructured text data in the banking sector has created a need for advanced classification methods to manage customer inquiries efficiently, resulting in faster response times, ...

In the field of optical character recognition, there are still unans wered research questions regarding the recognition of handwritten text. In this paper, an effective method for developing ...

Generating explanations for deep neural networks (DNNs) can make them more trustworthy in real-world applications. For a text classification task, existing methods visualize the contributions of words ...

LSTM captures long-range dependencies in sequential data, while CNN is effective at extracting localized features from text. This combination makes LSTM-CNN ideal for the complexity of Indonesian song ...

Text classification is an important problem in natural language processing. The main task is to divide the text into different categories according to the content of the text. This article ...

Semantic features encoded in the labels have a strong influence on multi-label text classification (MLTC) performance. This paper follows the assumption and proposes an MLTC approach with correlation ...

The overall accuracy of 99% underscores the models’ effectiveness in classification tasks, suggesting their potential for practical implementation in dental healthcare settings. Additionally, the ...