… The scheme will first accurately extract distal radius and ulna regions from hand radiographs,
… , our deep learning model finally achieves 90% and 92% recognition accuracies on radius …

… Long Short-Term Memory Network that can analyze human actions in real-time. This paper
… from NTU RGB + D action recognition datasets, such as brush hair, sit down, stand up, hand …

The concept of STREMIS visualization has been proven through user studies using methods
of photo elicitation, participatory observation, and interview with Taiwanese families at …

… on applying deep learning methods to medical image segmentation, particularly cardiac MRI
image … In deep supervised learning, we use neural network algorithms to train a model. The …

… (re-parameter squeeze-expand hand gesture recognition).通过使用结构重参数化方法,…
gesture areas and then identify them, while others directly use deep convolutional neural networks …

… In this paper, one-shot learning hand gesture recognition (OSLHGR) algorithm under the …
is studied through the cascade combination of deep convolutional neural networks (CNN). …

… of deep learning, the current status of image recognition of … on deep learning in vocal cord
image lesions recognition are … 使用卷积神经网络(Convolutional Neural Networks, CNNs)，逻辑…

… problem and the images of the machined surface in the surface quality inspection problem.
In both the problems, deep learning models using a convolutional neural network (CNN) are …