Computer Software and Media Applications

ISSN:

2578-1669 (Online)

Journal Abbreviation:

Comput. Soft. Media. Appl.

Computer Software and Media Applications (CSMA) is a peer-reviewed, open-access publication that delivers high-quality journal papers that are significant in all disciplines of computer software and media applications. With a focus on publishing high quality academic papers, detailing the latest information and research in the field of computer software and media applications. CSMA aims to provide a communication and information exchange platform for a broad audience of professionals. Articles from related fields that are interesting to a broad readership are particularly welcome.


 

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Computer Software and Media Applications is an Open Access Journal under EnPress Publisher. All articles published in Computer Software and Media Applications are accessible electronically from the journal website without commencing any kind of payment. In order to ensure contents are freely available and maintain publishing quality, Article Process Charges (APCs) are applicable to all authors who wish to submit their articles to the journal to cover the cost incurred in processing the manuscripts. Such cost will cover the peer-review, copyediting, typesetting, publishing, content depositing and archiving processes. Those charges are applicable only to authors who have their manuscript successfully accepted after peer-review.

Journal TitleAPCs
Computer Software and Media Applications$800

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Vol 5, No 1 (2022)

Table of Contents

Open Access
Original Research Article
Article ID: 1171
PDF
by Kun Fang
Comput. Soft. Media. Appl. 2022 , 5(1);    1956 Views
Abstract In the field of computer science, in order to realize the classification of images, a naive Bayes method based on multiple features has been proposed. This method is widely used and rich. It uses four features, such as extracting gray histogram features, SIFT features, SURF features, and reducing the dimensions of the dataset from data image sets. Naive Bayesian methods are used to obtain The accuracy, recall, and F1 value of the image for each feature. This paper analyzes the application and feature comparison of Naive Bayes method in images, and shows that image representation using SURF feature description can achieve better classification results.
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Open Access
Original Research Article
Article ID: 1172
PDF
by Peizheng Yang
Comput. Soft. Media. Appl. 2022 , 5(1);    496 Views
Abstract With the development of technology, IC has entered the era of VLSI. The internal circuit network structure is gradually complex, and the external threats are more and more.We can abstract the circuit in FPGA into complex network .Then characteristic is studied and the invulnerability is measured to optimize the circuit.
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More Articles>>

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