Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Abstract— Data compression has always been a key concern during transmission. Interests on image processing has been increased enormously from last decades. As a result different compression techniques has been introduced and purposed. Lossy image compression algorithms are used widely where some information gets lost during compression resulting high compression. However, we pay for their high compression rate with visual artifacts degrading the user experience. Deep convolutional neural networks (CNN) have become a widely used tool to address computer vision tasks very successfully.
"Image Compression on Heterogeneous Images Using Convolutional Neural Networks", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.5, Issue 8, page no.57 - 63, August-2020, Available :http://www.ijrti.org/papers/IJRTI2008010.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator