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Found 5 papers, 2 papers with code
[Re] Training Binary Neural Networks using the Bayesian Learning Rule
When we tried this in a semantic segmentation context, we found that the results were very underwhelming and in contrast with the seemingly good results by the STE optimizer even with much hyperparameter tuning.
Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement
Low light conditions in aerial images adversely affect the performance of several vision based applications.
Revisiting RCAN: Improved Training for Image Super-Resolution
Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight.
Nighttime Dehaze-Enhancement
Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner.
Utilizing Radiomic Feature Analysis For Automated MRI Keypoint Detection: Enhancing Graph Applications
One approach involves converting images into nodes by identifying significant keypoints within them.
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