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Automatic segmentation of breast cancer on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which reveals both temporal and spatial profiles of the foundational anatomy, plays a crucial role in the clinical diagnosis and treatment of breast cancer. Recently, deep learning has...
Convolutional neural networks (CNN) have been widely used in image super-resolution tasks in recent years, with remarkable results. Most existing CNN-based image super-resolution methods, on the other hand, deepen the network structure to increase the receptive field and do not fully utilize the...
Neural question generation (NQG) aims to generate a question from a given passage with neural networks. NQG has attracted more attention in recent years, due to its wide applications in reading comprehension, question answering, and dialogue systems. Existing works on NQG mainly use the...
Multiview granular data analytics reflects various aspects of the knowledge embodied in data by multiple granular structures. It has been investigated in many topics closely related to granular computing, especially those researches involving formal concept analysis. Three-way concept analysis...
In the application recommendation field, collaborative filtering (CF) method is often considered to be one of the most effective methods. As the basis of CF-based recommendation methods, representation learning needs to learn two types of factors: attribute factors revealed by independent...
Weakly supervised phrase grounding aims to map the phrases in an image caption to the objects appearing in the image under the supervision of image-caption correspondence. We observe that the current studies are insufficient to model the complicated interactions between the visual components...
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