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A study of traits that affect learnability in GANs
Generative Adversarial Networks GANs are algorithmic architectures that use two neural networks, pitting one against the opposite so as to come up with new, synthetic instances of data that can pass for real data.
Fast, Self Supervised, Fully Convolutional Color Normalization of H&E Stained Images
Performance of deep learning algorithms decreases drastically if the data distributions of the training and testing sets are different.
Machine Learning Techniques to Identify Hand Gestures amidst Forearm Muscle Signals
This study investigated the use of forearm EMG data for distinguishing eight hand gestures, employing the Neural Network and Random Forest algorithms on data from ten participants.
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