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All Outputs (3)

Learning from small and imbalanced dataset of images using generative adversarial neural networks. (2019)
Thesis
ALI-GOMBE, A. 2019. Learning from small and imbalanced dataset of images using generative adversarial neural networks. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

The performance of deep learning models is unmatched by any other approach in supervised computer vision tasks such as image classification. However, training these models requires a lot of labeled data, which are not always available. Labelling a ma... Read More about Learning from small and imbalanced dataset of images using generative adversarial neural networks..

Beyond the pixels: learning and utilising video compression features for localisation of digital tampering. (2019)
Thesis
JOHNSTON, P. 2019. Beyond the pixels: learning and utilising video compression features for localisation of digital tampering. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Video compression is pervasive in digital society. With rising usage of deep convolutional neural networks (CNNs) in the fields of computer vision, video analysis and video tampering detection, it is important to investigate how patterns invisible to... Read More about Beyond the pixels: learning and utilising video compression features for localisation of digital tampering..

Deep learning based approaches for imitation learning. (2018)
Thesis
HUSSEIN, A. 2018. Deep learning based approaches for imitation learning. Robert Gordon University, PhD thesis.

Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as well as rising demand for int... Read More about Deep learning based approaches for imitation learning..