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Found 4 papers, 1 papers with code
Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms
To collect our dataset, we build an image acquisition system to simultaneously capture geometrically aligned pairs of blurred and sharp images, and develop a postprocessing method to produce high-quality ground truth images.
Stochastic Adaptive Activation Function
The simulation of human neurons and neurotransmission mechanisms has been realized in deep neural networks based on the theoretical implementations of activation functions.
Explainable Deep Learning Algorithm for Distinguishing Incomplete Kawasaki Disease by Coronary Artery Lesions on Echocardiographic Imaging
Identifying coronary artery lesions by echocardiography is important for the timely diagnosis of and favorable outcomes in KD.
Self-Mutating Network for Domain Adaptive Segmentation in Aerial Images
By adopting Parameter Mutation to change the values of parameters and Parameter Fluctuation to randomly convulse the parameters, the network self-changes and fine-tunes the parameters, then achieves better predictions of a domain-adaptive segmentation.
