HIGHLIGHTS
- What: The model was trained using the LOL dataset and the results showed significant improvements in quality. Information about the learning dynamics and parameter changing capabilities of the model can be visualized by loss function graphs which aim to maximize picture quality. The aim is to increase the illumination in images taken in environments with low lighting conditions.
- Who: M. Diviya from the (UNIVERSITY) have published the research work: Enhancing low-illumination imagery using a Deep Convolutional Generative Adversarial Network with weight regularization (DCGAN-WR) and Zero-Reference Deep Curve Estimation (DCE), in the Journal . . .
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