Pamela Johnston
Title
Cited by
Cited by
Year
A review of digital video tampering: from simple editing to full synthesis
P Johnston, E Elyan
Digital Investigation 29, 67-81, 2019
132019
Symbols in engineering drawings (SIED): an imbalanced dataset benchmarked by convolutional neural networks
E Elyan, CF Moreno-García, P Johnston
International Conference on Engineering Applications of Neural Networks, 215-224, 2020
22020
Video tampering localisation using features learned from authentic content
P Johnston, E Elyan, C Jayne
Neural computing and applications, 1-15, 2019
22019
Spatial effects of video compression on classification in convolutional neural networks
P Johnston, E Elyan, C Jayne
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
22018
Toward video tampering exposure: inferring compression parameters from pixels
P Johnston, E Elyan, C Jayne
International Conference on Engineering Applications of Neural Networks, 44-57, 2018
12018
Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks
I Carloto, P Johnston, CJ Pestana, LA Lawton
Science of The Total Environment, 146956, 2021
2021
Pixel-based layer segmentation of complex engineering drawings using convolutional neural networks
CF Moreno-García, P Johnston, B Garkuwa
2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020
2020
Beyond the pixels: learning and utilising video compression features for localisation of digital tampering.
P Johnston
2019
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Articles 1–8