A New Multi-level Hazy Image and Video Dataset for Benchmark of Dehazing Methods-Reference-Cited by-同舟云学术

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A New Multi-level Hazy Image and Video Dataset for Benchmark of Dehazing Methods

Published:2023 Issue: Volume: Page:269-280
ISSN:2367-3370
Container-title:Fourth International Conference on Image Processing and Capsule Networks
language:
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Author:

Çetinkaya Bedrettin,Çimtay Yücel,Günay Fatma Nazli,Yılmaz Gökçe Nur

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-7093-3_18

Reference39 articles.

1. Sindagi VA, Oza P, Yasarla R, Patel VM (2020) Prior-based domain adaptive object detection for hazy and rainy conditions. In: Computer vision—ECCV 2020: 16th European conference, Glasgow, UK, August 23–28, 2020, proceedings, part XIV 16. Springer, pp 763–780

2. Li C, Liang X, Lu Y, Zhao N, Tang J (2019) rgb-t object tracking: benchmark and base-line. Pattern Recogn 96:106977

3. Pei Y, Huang Y, Zou Q, Lu Y, Wang S (2018) Does haze removal help CNN-based image classification? In: Proceedings of the European conference on computer vision (ECCV), pp 682–697

4. Hambarde P, Murala S (2020) S2dnet: depth estimation from single image and sparse samples. IEEE Trans Comput Imaging 6:806–817

5. Kaplan NH (2018) Remote sensing image enhancement using hazy image model. Optik 155:139–148

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1. A New Multi-level Hazy Image and Video Dataset for Benchmark of Dehazing Methods;Fourth International Conference on Image Processing and Capsule Networks;2023

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