Abstract: In the present era, Cancer-related deaths are predominantly driven by lung cancer globally, causing significant deaths across all demographics. Precise prediction and evaluation of treatment ...
Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...
Abstract: Leaf diseases are a major challenge for agricultural productivity, requiring accurate and efficient detection methods. This research presents an effective method for multi-class ...
Abstract: Chronic total occlusion (CTO) is a critical determinant of treatment efficacy in coronary artery disease, but its accurate diagnosis remains heavily reliant on the expertise of experienced ...
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: 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: Using dermoscopic images for the classification of skin lesion is crucial for early skin cancer detection, but resource limitations hinder complex deep learning model applications in ...
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: In recent years, unsupervised domain adaptation (UDA) based on deep learning has been widely applied to address the spectral shift problem in cross-scene hyperspectral image classification ...
Abstract: Identifying medicinal plants is crucial in herbal medicine, pharmaceutical research, and plant taxonomy. Conventional manual classification techniques tend to be errorprone and ...
Abstract: Skin diseases and it's infectious diseases are the most common health issues, requiring quick and correct diagnosis for appropriate treatment. In this study to describe the uses of ...