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Multiple fake classes GAN for data augmentation in face image dataset. (2019)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E. and JAYNE, C. 2019. Multiple fake classes GAN for data augmentation in face image dataset. In Proceedings of the 2019 International joint conference on neural networks (IJCNN 2019), 14-19 July 2019, Budapest, Hungary. Piscataway: IEEE [online], article ID 8851953. Available from: https://doi.org/10.1109/IJCNN.2019.8851953

Class-imbalanced datasets often contain one or more class that are under-represented in a dataset. In such a situation, learning algorithms are often biased toward the majority class instances. Therefore, some modification to the learning algorithm o... Read More about Multiple fake classes GAN for data augmentation in face image dataset..

Video tampering localisation using features learned from authentic content. (2019)
Journal Article
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2020. Video tampering localisation using features learned from authentic content. Neural computing and applications [online], 32(16): special issue on Real-world optimization problems and meta-heuristics and selected papers from the 19th Engineering applications of neural networks conference 2018 (EANN 2018), 3-5 September 2018, Bristol UK , pages 12243-12257. Available from: https://doi.org/10.1007/s00521-019-04272-z

Video tampering detection remains an open problem in the field of digital media forensics. As video manipulation techniques advance, it becomes easier for tamperers to create convincing forgeries that can fool human eyes. Deep learning methods have a... Read More about Video tampering localisation using features learned from authentic content..