Abstract: Glioma segmentation is a crucial task in computer-aided diagnosis, requiring precise discrimination between lesions and normal tissue at the pixel level. Popular methods neglect crucial edge ...

Abstract: Binary neural network (BNN) is an effective method for reducing model computational and memory cost, which has achieved much progress in the super-resolution (SR) field. However, there is ...

Detecting and responding appropriately to temporal changes in the shoreline is an important task for protecting coasts. Video monitoring has been utilized as a powerful tool for detecting shoreline ...

PyTorch implementations of the deep residual networks published in "Deep Residual Learning for Image Recognition" by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. The images were preprocessed by ...

The memristor-based convolutional neural network (CNN) gives full play to the advantages of memristive devices, such as low power consumption, high integration density, and strong network recognition ...

School of Computer Science and Technology, Tianjin Polytechnic University, Tianjin, China. At present, the art creation and animation creation process mainly uses sketching first, and then through a ...

p 複数のカーネルサイズのdilation conv層をclassification networkに付け足すことで、image-levelのオブジェクトラベルから、オブジェクトごとの密なlocalization mapを生成し、これを元にセマンティックセグメンテーションを行う手法を提案。image-levelのラベルのみが与え ...