Browsing Department of Computer Science and Engineering by Subject "Adversarial learning"
Now showing items 1-2 of 2
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STRUCTURE AWARE HUMAN POSE ESTIMATION USING ADVERSARIAL LEARNING
(2021-05-10)Pose estimation using Deep Neural Networks (DNNs) has shown outstanding performance in recent years, due to the availability of powerful GPUs and larger training datasets. However, there are still many challenges due to ... -
Towards Nuclei Segmentation with Limited Annotations
(2023-09-01)Nuclei segmentation is a fundamental but challenging task in histopathology image analysis. For semantic segmentation of nuclei, Convolutional Neural Network (CNN), and Vision Transformer (VT) models give very promising ...