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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1137
Title: End-to-end deep network for image denoising and colorization
Authors: Khoa Van Tran 
Dinh Quang Vinh 
Phuc Hong Nguyen 
Narayan DEBNATH C 
Nguyen Tuan Duc 
Chang Wook Ahn 
Keywords: Image denoising;Colorization;Deep network
Issue Date: 2020
Source: http://manuscriptlink-society-file.s3.amazonaws.com/kism/conference/sma2020/presentation/SMA-2020_paper_39.pdf
Conference name: The 9th International Conference on Smart Media and Application 
Abstract: 
This paper proposes a deep neural network that solves the denoising and colorization problem simultaneously. The joint problem is solved by two separate sub-networks that are trained in an end-to-end manner. Specifically, map attention modules are used to revise feature maps, while a few convolutional layers to extract features at the beginning of the network helps to boost the proposed network significantly. We use KITTI dataset to prepare training and testing datasets. In addition, we compare the proposed method with the baseline method using the PSNR and SSIM metrics. To have a fair comparison, we train the proposed and baseline methods using the same dataset, loss function, and training configurations. The experimental results show that the proposed method performed significantly better the baseline method in the KITTI dataset
Duration: 17-19/9/2020
Conference venue: Jeju, Korea
URI(1): http://epub.vgu.edu.vn/handle/dlibvgu/1137
Appears in Collections:Conference papers

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