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Single Image Super-Resolution Using ConvNeXt

2022 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2022
Chenghui You   +3 more
openaire   +1 more source

Rectified Binary Network for Single-Image Super-Resolution

IEEE Transactions on Neural Networks and Learning Systems
Binary neural network (BNN) is an effective approach to reduce the memory usage and the computational complexity of full-precision convolutional neural networks (CNNs), which has been widely used in the field of deep learning. However, there are different properties between BNNs and real-valued models, making it difficult to draw on the experience of ...
Jingwei Xin   +5 more
openaire   +3 more sources

Real-world single image super-resolution: A brief review

Information Fusion, 2022
Honggang Chen, Xiaohai He, Linbo Qing
exaly  

Single-image super-resolution enhancement mechanism

AIP Conference Proceedings, 2022
P. V. Pramila   +4 more
openaire   +1 more source

Single-molecule localization microscopy

Nature Reviews Methods Primers, 2021
Mickael Lelek   +2 more
exaly  

Memory-efficient single-image super-resolution

Big Data IV: Learning, Analytics, and Applications, 2022
Nicholas Chiapputo, Colleen P. Bailey
openaire   +1 more source

Single Image Super Resolution Using AI Generated Images

Image super-resolution has become increasingly important in various applications because of their demand for producing high output images from the low input images. Earlier for the image enhancements techniques like deblurring were performed to get the quality image.
Khan, Faisal Rasheed   +2 more
openaire   +1 more source

Single Frame Super-Resolution Imaging

Zhe Wang, Zhengjun Liu, Yutong Li
openaire   +1 more source

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