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: 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: 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 ...
Brightness-Enhanced Gastrointestinal Endoscopy Image Classification Using CNN-Based Diagnostic Model
Abstract: This study proposes a framework based on a Cycle-Consistent Generative Adversarial Network (CycleGAN) to improve the image brightness and visual continuity of gastrointestinal (GI) ...
Abstract: Yoga is an ancient exercise consisting of various postures called asanas. Yoga improves physical, mental and spiritual well-being of the person. Yoga pose classification includes the ...
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: During the last decade, the deep learning depending upon the Convolutional Neural Network (CNN) structure has been demonstrated as an efficient approach to classify different objects ...
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