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Conversion and Implementation of State-of-the-Art Deep Learning Algorithms for the Classification of Diabetic Retinopathy
In this paper, comprehensive experimental studies of implementing state-of-the-art CNNs for the detection and classification of DR are conducted in order to determine the top performing classifiers for the task.
Instance-based Deep Transfer Learning
It makes use of pre-trained models that are learned from a source domain, and utilizes these models for the tasks in a target domain.
An ELU Network with Total Variation for Image Denoising
In this paper, we propose a novel convolutional neural network (CNN) for image denoising, which uses exponential linear unit (ELU) as the activation function.
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