Journal La Multiapp

Journal La Multiapp

Survey on CNN based super resolution methods

Yazarlar: Rafaa Amen Kazem, Jamila H. Suad, Huda Abdulaali Abdulbaqi

Cilt 2 , Sayı 4 , 2021 , Sayfalar 27-33

Konular:-

DOI:10.37899/journallamultiapp.v2i4.444

Anahtar Kelimeler:CNN,VSDR,FSRCNN,DRCN

Özet: Super Resolution is a field of image analysis that focuses on boosting the resolution of photographs and movies without compromising detail or visual appeal, instead enhancing both. Multiple (many input images and one output image) or single (one input and one output) stages are used to convert low-resolution photos to high-resolution photos. The study examines super-resolution methods based on a convolutional neural network (CNN) for super-resolution mapping at the sub-pixel level, as well as its primary characteristics and limitations for noisy or medical images.

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@article{2021, title={Survey on CNN based super resolution methods}, volume={2}, number={27–33}, publisher={Journal La Multiapp}, author={Rafaa Amen Kazem,Jamila H. Suad,Huda Abdulaali Abdulbaqi}, year={2021} }
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Rafaa Amen Kazem,Jamila H. Suad,Huda Abdulaali Abdulbaqi. (2021). Survey on CNN based super resolution methods (Vol. 2). Vol. 2. Journal La Multiapp.
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Rafaa Amen Kazem,Jamila H. Suad,Huda Abdulaali Abdulbaqi. Survey on CNN Based Super Resolution Methods. no. 27–33, Journal La Multiapp, 2021.
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