DEEP LEARNING BASED IMAGE SUPER RESOLUTION TO ENHANCE LOW QUALITY IMAGE

Registration ID: IJNRD_186600

Published ID: IJNRD2301295

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Dr. V.Vijayakumar, M.Tech,Ph.D, S.kaviya, P.keerthana

Single image super-resolution, deep learning, neural networks, objective function

Images of high decision and coffee quality create extensive problems in fixing the troubles of visible reputation of items for commentary and navigation necessary for diverse navy and civil functions. The noise ratio (SNR) and root imply square blunders (MSE) of decision pics have improved substantially because of latest traits in deep getting to know strategies together with EDSR and VDSR. However, there might not be an immediate courting between those pixel-domain signal quality measures and machine imaginative and prescient tasks which include object popularity and landmark detection. . Beyond the technical solution that complements gradient photographs and associated functions from low resolution photos for the gain of high system imaginative and prescient is the focal point of this work. A answer for ultra- excessive decision gradient imaging is advanced right here. The simulation outcomes display overall performance profits in terms of factor repeatability and gradient picture fine.

Published Paper   E-Certificate

Dr. V.Vijayakumar, M.Tech,Ph.D, S.kaviya, & P.keerthana (January-2023). DEEP LEARNING BASED IMAGE SUPER RESOLUTION TO ENHANCE LOW QUALITY IMAGE. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(1), c744-c751. https://ijnrd.org/papers/IJNRD2301295.pdf

Volume 8 Issue 1, January-2023

Pages : c744-c751

Paper Reg. ID: IJNRD_186600

Published Paper Id: IJNRD2301295

Downloads: 000121988

Research Area: Electronics & Communication Engg. 

Author Type: Indian Author

Country: Chennai, Tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2301295.pdf

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