Abstract: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical importance of early and accurate detection in improving patient outcomes and treatment ...
Abstract: With the ease of classifying land through satellite imaging, remote sensing has captured the Earth observation domain. Traditional methods for analyzing satellite images relied on manual ...
Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
Abstract: As powerful image editing software are more readily available, authentication of digital images poses a great problem. Most older forgery detection techniques relying on metadata inspection ...
Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...
Abstract: A research project focuses on creating automated trash detection and classification through convolutional neural networks (CNNs) with an objective to improve waste management systems. The ...
Abstract: This letter proposes KAN-based multispectral image super-resolution method (KMSR), a novel deep learning framework for multispectral image (MSI) super-resolution (SR) that integrates ...
Abstract: Various lesions in different body parts have different sizes and, in particular, different representations, which leads to great challenges for medical image classification tasks. To avoid ...
Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
Abstract: Pneumonia is one of the most serious lung infections and remains a leading cause of death in children under five years of age, especially in developing countries such as Indonesia. Diagnosis ...
Abstract: With the widespread use of Internet services, the risk of cyber attacks has increased significantly. Existing anomaly-based network intrusion detection systems suffer from slow processing ...
Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...
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