However, to make these digital learning sessions interactive and comparable to the traditional offline classrooms, it is essential to ensure that students are properly engaged during online classes. In this paper, we have presented novel deep learning based algorithms that monitor the student’s ...
in the high-dimensional data is difficult to discover using conventional machine learning algorithms.In biology,applications of deep learning are gaining increasing popularity in predicting the structure and function of genomic elements,such as promoters,enhancers,or gene expression levels.In this review ...
The deep learning is a new learning method of the machine learning, it simulates the human brain and analysis the neural network through the imitation of the human brain and the interpretation of the relevant data. In the text mining, the application of the deep learning can be a very good...
Application of deep learning methods in speech enhancement 语音增强中的深度学习应用 按: 本文是DNS,AEC,PLC等国际级语音竞赛的主办方——Microsoft Research Labs音频与声学研究组(Audio and Acoustics Research Group)于2021年发表的Sound capture and speech enhancement for speech-enabled devices中节选的一章,总结...
COVID-19 Detection X-Rays Deep learning Convolutional neural network (CNN) nCOVnet 1. Introduction Research investigations show that around dozens of viruses exist in the family of the corona, but only seven types are dangerous to human beings [1]. It is noted that these viruses are transmitte...
In this paper, we introduce a deep learning-enabled mobile application which can run entirely on common low-cost smartphones for efficient and robust herb image recognition with a quite competitive recognition accuracy in resource-limited situations. We hope this application can make contributions to ...
如果NN很deep,则 gradients explode 梯度爆炸式增长 W^{[l]}=\left[\begin{array}{cc} 0.5 & 0 \\ 0 & 0.5 \end{array}\right],\forall l \in [L-1] 则\hat{y}=W^{[L]}\left[\begin{array}{ll}0.5 & 0 \\ 0 & 0.5\end{array}\right]^{l-1} x ...
You will use use the functions you'd implemented in the previous assignment to build a deep network, and apply it to cat vs non-cat classification. After this assignment you will be able to: Build and apply a deep neural network to supervised learning. ...
Deep learning-based radiomics had yet to be incorporated for the automated prediction of curve progression. Added value of this study This study combines recent advances in machine learning with our understanding on curve morphology in adolescent idiopathic scoliosis (AIS). We reveal that postero...
Herein we introduce a deep learning (DL) application engine (DLAE) system concept, present potential uses of it, and describe pathways for its integration in clinical workflows. An open-source software application was developed to provide a code-free approach to DL for medical imaging applications...