Vol 4, No 1

Open Access

Original Research Articles

Article ID: 886

Application Research of Deep Convolutional Neural Network in Computer Vision

by Lei Wang

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 269 Views, 9 PDF Downloads

As an important research achievement in the field of brain like computing, deep convolution neural network has been widely used in many fields such as computer vision, natural language processing, information retrieval, speech recognition, semantic understanding and so on. It has set off a wave of neural network research in industry and academia and promoted the development of artificial intelligence. At present, the deep convolution neural network mainly simulates the complex hierarchical cognitive laws of the human brain by increasing the number of layers of the network, using a larger training data set, and improving the network structure or training learning algorithm of the existing neural network, so as to narrow the gap with the visual system of the human brain and enable the machine to acquire the capability of “abstract concepts”. Deep convolution neural network has achieved great success in many computer vision tasks such as image classification, target detection, face recognition, pedestrian recognition, etc. Firstly, this paper reviews the development history of convolutional neural networks. Then, the working principle of the deep convolution neural network is analyzed in detail. Then, this paper mainly introduces the representative achievements of convolution neural network from the following two aspects, and shows the improvement effect of various technical methods on image classification accuracy through examples. From the aspect of adding network layers, the structures of classical convolutional neural networks such as AlexNet, ZF-Net, VGG, GoogLeNet and ResNet are discussed and analyzed. From the aspect of increasing the size of data set, the difficulties of manually adding labeled samples and the effect of using data amplification technology on improving the performance of neural network are introduced. This paper focuses on the latest research progress of convolution neural network in image classification and face recognition. Finally, the problems and challenges to be solved in future brain-like intelligence research based on deep convolution neural network are proposed.

Open Access

Original Research Articles

Article ID: 906

Signal Processing from the First Exploration of Big Data Horizon

by Jin Shi

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 170 Views, 7 PDF Downloads

Under the background of the popularization and application of computers in various fields, the amount of diversified data has been greatly increased, which also means that the era of big data is gradually coming. At the same time, various signal equipment and sensor equipment are widely used in various fields. People from the perspective of big data expect to collect, analyze and process the signal data by means of big data. However, due to the diversity of signal data and the huge and complex amount of data, the future development trend of signal from the perspective of big data is the information fusion of signal data. Therefore, it is necessary to explore signal processing from the perspective of big data. With the application of signal processing technology, the efficiency and quality of information processing can be improved gradually.

Open Access

Original Research Articles

Article ID: 1096

Research on Trust Evaluation Model Based on Statistical Data in E-Commerce

by Yushui Xiao, Norriza Binti Hussin

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 172 Views, 7 PDF Downloads

Both the level of science and technology and people’s economic level have been significantly improved in the present social background. With the application and popularization of computers and networks in people’s homes, online shopping, which is of high flexibility and convenience, has emerged and gradually become an important choice to shop. In e-commerce activities, the trust between the two parties often directly affects the results of online transactions, which is even a very critical influencing factor. Therefore, an effective trust evaluation model will make a positive impact on the healthy and sustainable development of e-commerce activities. Based on the trust evaluation model of reputation that has been applied in practice, this article will integrate D-S evidence fusion algorithm into the new evaluation model and try to analyze its unique value in application.

Open Access

Original Research Articles

Article ID: 1102

Data and Information Security Technology in Network Communication

by Mengqi Li

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 320 Views, 12 PDF Downloads

With the continuous innovation of science and technology, data and information security technology is widely used in various industries. The application of this technology can obviously enhance the security of network communication. This article discusses the significance and insecurity of network information security, and puts forward some measures for protecting data and information security for the reference.

Open Access

Original Research Articles

Article ID: 1103

Reflection on Prevention and Control of Telecommunication Network Fraud in Big Data Era

by Xingrui Wang

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 571 Views, 39 PDF Downloads

With the rapid development of smart phones and communication technology, the frequency of communication between the public and society through telecommunication equipment is increasing. At the same time, some lawless elements often cheat the public through telecommunication equipment, which brings irreparable economic losses to the society and the masses to a certain extent. In view of the above problems, this article takes the source of telecommunication fraud as the breakthrough point, analyzes the existing telecommunication fraud processing technology and points out its shortcomings, and then proposes a method of telephone fraud analysis based on big data technology. This technology fills the defects of the existing telecommunication interception technology and provides a new idea for effectively avoiding telecommunication fraud in the future.

Open Access

Original Research Articles

Article ID: 1107

Evaluating on Topology Survivability Based on Largest Number of Node-Disjoint Paths

by Qiurong Chen

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 166 Views, 8 PDF Downloads

On the point of view of Largest Number of Node-Disjoint Path (LNNDP for short) between a node pair in a network, this article states the importance of LNNDP to global survivability of topology at first, then proposes an algorithm to compute maximal number of node-disjoint paths between node pairs. A new topology survivability metric based on LNNDP is put forward to evaluate the global survivability of network topology. It can be used to evaluate the survivability of topology provided. This metric can express accurately global topology survivability.