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An Image Deblurring Method Using Improved U-Net Model
2022
Mobile Information Systems
Deblurring methods in dynamic scenes are a challenging problem. Recently, significant progress has been made for image deblurring methods based on deep learning. However, these methods usually stack ordinary convolutional layers or increase convolution kernel size, resulting in limited receptive fields, an unsatisfying deblurring effect, and a heavy computational burden. Therefore, we propose an improved U-Net (U-shaped Convolutional Neural Network) model to restore the blurred images. We first
doi:10.1155/2022/6394788
fatcat:gl5yrvh7jjej5mhkv4rbzhavvi