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Application Research of Deep Convolutional Neural Network in Computer Vision

by Lei Wang

Journal of Networking and Telecommunications, Vol.4, No.1, 2022; 367 Views

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 â€œabstract conceptsâ€. 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.

Analysis of Computer Network Security and Preventive Measures in the Data Age

by Zhi Li

Journal of Networking and Telecommunications, Vol.2, No.1, 2020; 333 Views

With the development of science and technology, the network in human society continues to be improvedÂ and enriched, as well as the ability of database technology, which is ofÂ super cloud computing ability and extensive data sharing and bringsÂ great convenienceÂ toÂ the whole country. But at the same time, the data that is used improperlyÂ in the network environment not only poses a certain threat to the network system, but also gradually erodes people's lives. For the computer network security problems in the era of big data, this paper first analyzes the location of the problems, andÂ then puts forward the means to solve and prevent the security problems.

Research on Computer Applications Based on Management of Network Information Security Technology

by Xiaofeng Ma, Norriza Hussin

Journal of Networking and Telecommunications, Vol.5, No.1, 2023; 395 Views

With the rapid development of computer network, the fully opened network has greatly changed peopleâ€™s production and daily life and the traditional industries are no longer closed. However, there are also many network security problems. To deal with it, this article explores the computer applications based on management of network information security technology. It analyzes the main factors threatening network information security from the security problems caused by computer applications. Combining with the application practice, specific measures are put forward for reference.

Simple Analysis of Pipeline Performance and Cycle Optimization in Computer Architecture

by Shaoshao Xu

Journal of Networking and Telecommunications, Vol.3, No.1, 2021; 159 Views

This paper first summarizes the performance analysis of pipeline and some problems related to the performance of pipeline, and then introduces the how to loop optimization in detail. Pipelining technology is a very important technology in the field of computer. Using pipelining technology, multiple executing device in the computer work in parallel. The idea of parallelism comes from the traditional production assembly-line model of factory. As early as in the 1960s, some high-end machines have begun to use pipeline technology. Up to now, the pipeline technology has been very mature. The IBM7030 was the first computer to adopt pipeline technology. Pipelined processor can meet the higher requirements of computer operation and improve the performance of CPU. Pipelined processor has become an important and indispensable part of computer architecture.

SDL Trados and Tmxmall: A Comparative Study of Computer-Aided Translation Tools

by Ran Cheng

Journal of Networking and Telecommunications, Vol.6, No.1, 2024; 381 Views

Technological development has brought about a series of changes, including influences on the traditional translation industry which is unable to meet the future needs due to its low efficiency and limited forms. Computer-aided translation software, shortened as CAT software, is therefore developed. Featuring powerful memory and fast computing speed of computers, CAT software allows translators to give full scope to creativity, which enhances traditional translation efficiency. In recent years, both CAT software and cloud translation software have been rapidly developed. The latter is built based on cloud computing technology, and is emerging one after another. This article, taking such CAT software as SDL Trados and such cloud translation platform as Tmxmall as examples, studies similarities and differences between the two different kinds of tools in terms of operation interface, translation project management and corpus management. By analyzing features of the two tools, this article seeks to provide references for translators and software engineers.

Design of Human-Computer Interaction Control System Based on Steady-state Visual Evoked Encephalography (SSVEP)

by Leipo Liu

Journal of Networking and Telecommunications, Vol.6, No.1, 2024; 88 Views

With the continuous development of science and technology, the research of EEG has gradually made great achievements. During this time, a technique called mechanized brain interface was also being used. This technology is based on the computer technology, using the EEG signals generated by the neural activities of the human brain to link with the external devices, so as to form a brain as the signal source, through the signal transmission to the external devices to control the external devices of an emerging technology. The visual system collects information from the outside world, and the EEG signals transmit these signals to the brain. Finally, the brain analyzes and makes judgments so as to give instructions to the mechanical parts, and finally the mechanical parts realize the effect. The experiment found that the system can accurately collect the visual information and the generated EEG signals can be timely display conversion, and finally these signals will be converted into digital signals sent to the calculation of the processing system. In this paper, human-computer interaction control as the entry point, through the analysis and design of the EEG signals of the human brain, and finally designed the ability system that can enable people with physical disabilities to obtain autonomous activities.

Application Research of Computer Technology in Office Automation

by Xiuli Lu, Zhou Yang, Yan Wang, Yongli Liu

Journal of Networking and Telecommunications, Vol.6, No.1, 2024; 246 Views

With the rapid development of global economic integration, people all over the world can communicate with their friends and colleagues through computers, which not only brings convenience to people's lives, but also brings great convenience to their work. Industries, enterprises have to face increasingly complex tasks, their work ability and comprehensive quality requirements are also increasing. The traditional management concept and management mode can not adapt to the needs of enterprise office automation. The enterprise should keep pace with the Times, flexible use of computer technology, further improve the efficiency of office automation.