In the training set, on-the-fly intensity and geometry augmentation was applied to avoid overfitting. The batch was set to 32 for 200 epochs and the initial learning rate was 1e-3 with a decay factor of 0.9 every 10 epochs. Adam optimizer was applied to update the model parameters (...
In Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, 13–19 June 2020; pp. 1777–1786. [Google Scholar] [CrossRef] Wang, Y.; Wan, R.; Yang, W.; Li, H.; Chau, L.P.; Kot, A.C. Low-Light Image Enhancement with ...
Data augmentation was carrying out with the Caffe method DL detection: Fast R-CNN, multiscale-DBN, and random forest; DL segmentation: CRF; DL classification: regression method. Segmentation with GAN learning. An SDAE (OverFeat) model was used to classify with the ensemble method. Application ...
The computational cost and time required for each simulation are high. For this reason, it was decided to select these five models that have been widely used in the literature. However, to the best of our knowledge, there is no exhaustive statistical analysis in the literature that attempts ...