Low illumination underwater light field images reconstruction using deep convolutional neural networks

By Yujie Li, Tomoki Uemura, Hyoungseop Kim, Seiichi Serikawa. 2018

271 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Peixian Zhuang
2. Chongyi Li
3. Xipeng Pan
4. Ling Zhou
5. Weidong Zhang
6. Wenyi Zhao
7. Guohou Li
8. Yuehan Chen

In Media Technology

1. Peixian Zhuang
2. Chongyi Li
3. Peng Jiang
4. Yujie Li
5. Bin Liu

Citations in the corpus

• NAS-Unet: Neural Architecture Search for Medical Image Segmentation (2019, methodology): “[15] H. Lu et al. (2018).”
• Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networks (2019, background): “Because CNNs can extract features automatically and directly from the input images, thereby avoiding complex preprocessing on images, they have been a research hotspot in object detection [15], [16].”
• Underwater Image Enhancement via Weighted Wavelet Visual Perception Fusion (2024, background): “On the one hand, light absorption easily leads to color cast, low contrast, and brightness reduction in underwater images [3].”