搜索图像增强共有 15 个结果
1
Unsupervised raw infrared image enhancement based on layer decomposition
优先出版
2025年第8期 :
doi:10.19734/j.issn.1001-3695.2024.11.0509
2
Review of low light image enhancement based on deep learning
2025年第1期 : 19-27
doi:10.19734/j.issn.1001-3695.2024.06.0176
3
EnGAN: enhancement generative adversarial network in medical image segmentation
2024年第7期 : 2195-2202
doi:10.19734/j.issn.1001-3695.2023.08.0509
4
Dark light image enhancement network for machine vision perception
2024年第6期 : 1910-1915
doi:10.19734/j.issn.1001-3695.2023.08.0404
5
MaskMix:mask mixing augmentation method for change detection
2023年第12期 : 3834-3840,3847
doi:10.19734/j.issn.1001-3695.2023.06.0228
6
Underwater image enhancement networks incorporating self-calibrated illumination frame
2023年第11期 : 3490-3495
doi:10.19734/j.issn.1001-3695.2023.04.0124
7
Multiple description coded image enhancement method with joint learning of side-decoding and central-decoding features
2022年第9期 : 2873-2880
doi:10.19734/j.issn.1001-3695.2022.02.0061
8
Vehicle detection method based on MobileVit lightweight network
2022年第8期 : 2545-2549
doi:10.19734/j.issn.1001-3695.2021.12.0684
9
PNet:multi-level low-illumination image enhancement network based on attention mechanism
2022年第5期 : 1579-1585
doi:10.19734/j.issn.1001-3695.2021.09.0384
10
Low-light image enhancement based on multi-branch residual and affine transformation
2021年第12期 : 3786-3790,3807
doi:10.19734/j.issn.1001-3695.2021.03.0126
11
Survey of underwater image enhancement and restoration algorithms
2021年第9期 : 2561-2569,2589
doi:10.19734/j.issn.1001-3695.2020.11.0545
12
Coyote optimization algorithm with global guidance and coyote interaction and its application
2020年第9期 : 2711-2717
doi:10.19734/j.issn.1001-3695.2019.04.0136
13
Multi-level decomposition Retinex low-light image enhancement algorithm
2020年第4期 : 1204-1209
doi:10.19734/j.issn.1001-3695.2018.07.0788
14
Image enhancement method based on multi-layer fusion and detail recovery
2020年第2期 : 584-587
doi:10.19734/j.issn.1001-3695.2018.06.0572
15
New approach to segment retinal vessel using morphology and Otsu
2019年第7期 : 2228-2231
doi:10.19734/j.issn.1001-3695.2018.01.0122