Browsing Department of Computational and Data Sciences (CDS) by Subject "Generative Adversarial Networks"
Now showing items 1-2 of 2
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Deep Learning for Hand-drawn Sketches: Analysis, Synthesis and Cognitive Process Models
Deep Learning-based object category understanding is an important and active area of research in Computer Vision. Most work in this area has predominantly focused on the portion of depiction spectrum consisting of ... -
Deep Visual Representations: A study on Augmentation, Visualization, and Robustness
Deep neural networks have resulted in unprecedented performances for various learning tasks. Particularly, Convolutional Neural Networks (CNNs) are shown to learn representations that can efficiently discriminate hundreds ...