Výsledky vyhledávání - Image Dehazing Encoder and Decoder Network Generative Adversarial Network Multi

An Attention Encoder-Decoder Network Based on Generative Adversarial Network for Remote Sensing Image Dehazing Autor Zhao, Liquan, Zhang, Yupeng, Cui, Ying

“… It can be regarded as the preprocessing of high-level tasks of remote sensing images. To remove haze from the hazy remote sensing image, an encoder-decoder based on generative adversarial network is proposed…”
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CGGAN: a context-guided generative adversarial network for single image dehazing Autor Zhou, Zhaorun, Shi, Zhenghao

“…Image haze removal is highly desired for the application of computer vision. This study proposes a novel context-guided generative adversarial network (CGGAN…”
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Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network Autor Zhao, Liquan, Yin, Yanjiang, Zhong, Tie, Jia, Yanfei

“… To effectively mitigate the impact of haze on image quality, we propose an unsupervised generative adversarial network specifically designed for remote sensing image dehazing…”
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Self-supervised polarization image dehazing method via frequency domain generative adversarial networks Autor Sun, Rui, Chen, Long, Liao, Tanbin, Fan, Zhiguo

“… In this work, we propose a self-supervised polarization image dehazing framework based on frequency domain generative adversarial networks…”
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Single image dehazing via cycle-consistent adversarial networks with a multi-scale hybrid encoder-decoder and global correlation loss Autor Yao, Tingting, Liang, Yue, Zhang, Lelin, Xia, Na, Hu, Qing

“… In this paper, we propose a novel image dehazing method for unpaired data via cycle-consistent adversarial networks with a multi-scale hybrid encoder-decoder and global correlation loss…”
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UTCR-Dehaze: U-Net and transformer-based cycle-consistent generative adversarial network for unpaired remote sensing image dehazing Autor Li, Canlin, Zhang, Xiangfei, Wang, Hua, Shao, Zhiwen, Ma, Lizhuang

“… Generative Adversarial Network for unpaired remote sensing image dehazing (UTCR-Dehaze). In this model, considering that paired hazy images are difficult to obtain, a cycle-consistent generative adversarial network (CycleGAN…”
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CGGAN: A Context Guided Generative Adversarial Network For Single Image Dehazing Autor Zhou, Zhaorun, Shi, Zhenghao, Guo, Mingtao, Feng, Yaning, Zhao, Minghua

“…Image haze removal is highly desired for the application of computer vision. This paper proposes a novel Context Guided Generative Adversarial Network (CGGAN…”
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Encoder-Recurrent Decoder Network for Single Image Dehazing Autor Dang, An, Vu, Toan H., Wang, Jia-Ching

“…This paper develops a deep learning model, called Encoder-Recurrent Decoder Network (ERDN…”
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Attentive U-recurrent encoder-decoder network for image dehazing Autor Yin, Shibai, Wang, Yibin, Yang, Yee-Hong

“…•The U-recurrent encoder-decoder network predicts the clear image with the guidance of the haze attention map…”
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Attention-Based Encoder-Decoder Network For Single Image Dehazing Autor Gao, Shunan, Zhu, Jinghua, Xi, Heran

“… To solve the above problems, we propose an end-to-end Attention-based Encoder-Decoder Network (AEDNet…”
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A Novel Approach to Maritime Image Dehazing Based on a Large Kernel Encoder–Decoder Network with Multihead Pyramids Autor Yang, Wei, Gao, Hongwei, Jiang, Yueqiu, Zhang, Xin

“…–decoder network with multihead…”
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Encoder-decoder networks with guided transmission map for effective image dehazing Autor Tran, Le-Anh, Park, Dong-Chul

“…A plain-architecture and effective image dehazing scheme, called Encoder-Decoder Network with Guided Transmission Map (EDN-GTM…”
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Encoder and Decoder-Based Feature Fusion Network for Single Image Dehazing Autor Shit, Sahadeb, Das, Dibyendu Kumar, Sur, Amit, Ray, Dip Narayan, Banik, Bipasha Chakrabarti, Rana, Aiswarya

“… To that aim, we propose an encoder-decoder model that combines feature fusion with channel and color attention to improve real-time dehazing performance…”
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A novel encoder-decoder network with guided transmission map for single image dehazing Autor Tran, Le-Anh, Moon, Seokyong, Park, Dong-Chul

“…A novel Encoder-Decoder Network with Guided Transmission Map (EDN-GTM) for single image dehazing scheme is proposed in this paper…”
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A Novel Encoder-Decoder Network with Guided Transmission Map for Single Image Dehazing Autor Le-Anh, Tran, Moon, Seokyong, Park, Dong-Chul

“…A novel Encoder-Decoder Network with Guided Transmission Map (EDN-GTM) for single image dehazing scheme is proposed in this paper…”
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Sequentially Refined Spatial and Channel-Wise Feature Aggregation in Encoder-Decoder Network for Single Image Dehazing Autor Chen, Xuesong, Lu, Haihua, Cheng, Kaili, Ma, Yanbo, Zhou, Qiuhao, Zhao, Yong

“… Because they just employ the convolutional neural network (CNN) as an end-to-end mapping module, generating dehazed image directly or learning parameters in atmospheric…”
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Encoder-decoder networks with guided transmission map for effective image dehazing: Encoder-decoder networks Autor Tran, Le-Anh, Park, Dong-Chul

“…A plain-architecture and effective image dehazing scheme, called Encoder-Decoder Network with Guided Transmission Map (EDN-GTM…”
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Dehazing Underwater Images Using Encoder Decoder Based Generic Model-Agnostic Convolutional Neural Network Autor Thomas, Rosemol, Thampi, Lidiya, Kamal, Suraj, Balakrishnan, Arun A., Mithun Haridas, T. P., Supriya, M. H.

“… Moreover automatic analysis of marine digital data has a high research demand. This paper aims to introduce a fully connected convolutional neural network for dehazing underwater images…”
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Efficient Image Dehazing Using an Encoder-Decoder Network with Residual Learning Autor Pathak, Arpit, Singh, Om Prakash, Purkayastha, Sharbani, Biswas, Ujjwal

“… In this study, we present an effective framework for image dehazing that improves image clarity by utilizing multi-scale feature extraction and an encoder-decoder network with residual connections…”
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DHGAN: Generative adversarial network with dark channel prior for single‐image dehazing Autor Wu, Wenxia, Zhu, Jinxiu, Su, Xin, Zhang, Xuewu

“… To overcome these weaknesses, we propose an image‐to‐image dehazing model based on generative adversarial networks (DHGAN…”
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