Research Article
Research on Convolutional Neural Network Based on Deep Learning Framework in Big Data Education
@INPROCEEDINGS{10.1007/978-3-030-87903-7_16, author={Xuan Luo}, title={Research on Convolutional Neural Network Based on Deep Learning Framework in Big Data Education}, proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1--3, 2021, Proceedings, Part II}, proceedings_a={BIGIOT-EDU PT2}, year={2021}, month={10}, keywords={Deep learning Artificial neural network Convolutional neural network Deep learning framework Caffe}, doi={10.1007/978-3-030-87903-7_16} }- Xuan Luo
Year: 2021
Research on Convolutional Neural Network Based on Deep Learning Framework in Big Data Education
BIGIOT-EDU PT2
Springer
DOI: 10.1007/978-3-030-87903-7_16
Abstract
Deep learning is an important part of the development of artificial intelligence. Deep learning has made breakthroughs in many fields (such as image recognition, speech recognition, natural language processing), and has made gratifying achievements in the application of traditional algorithms which are not easy to solve, It includes automatic driverless vehicle, automatic pattern recognition, automatic simultaneous interpretation, commodity image retrieval, handwritten character recognition, license plate recognition, etc. In recent years, with the continuous improvement of research and development personnel’s requirements for deep learning development process, the traditional deep learning programming methods can not meet the current needs. The traditional deep learning programming methods will take researchers and developers months or even years to implement the most basic algorithms. At the same time, the traditional deep learning programming methods can not meet the current needs, In this paper, a variety of in-depth learning frameworks, including CAE, have been developed for some of the world’s top research institutions. These deep learning frameworks not only provide efficient and fast development models for scientific research institutions and related developers, but also provide several convolutional neural network models for developers to study and improve on the more advanced and perfect convolutional neural network models.