Image Deblurring Using Non Linear Activation Free Network
Year: 2024
Type: article
Abstract: : While picture restoration has made significantstrides in recent years, the sophisticated techniques employed are becoming more intricate. This makes a proper comparison difficult. In this research, we propose a straightforward approachthat outperforms these intricate ones in terms of accuracy while requiring less computational resources. We discovered that complex activation functions such as GELU, Softmax, ReLU, andSigmoid are not really needed. Therefore, we developed a more basic version that does not need them, which we call NAFNet.We put our approach to the test on challenging tasks such as noise reduction and image correction. It performed much better, far better than the sophisticated techniques, and used a lot less processing power.
Authors: Prof. S. S. Nalawade, Rupesh D. Shivgan, Prajakta A. Godkar, Bhakti R. Prabhu
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404002927