Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158878
Title: Deep learning-based image forgery detection
Authors: Lu, Ye
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Lu, Y. (2022). Deep learning-based image forgery detection. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158878
Abstract: In recent years, different kinds of image synthesis models have been developed, which are widely used in the field of deep learning and daily life. However, many people are troubled by these techniques because they can be utilized by malicious people to produce fake images. Nevertheless, different image synthesis techniques emerge one after another, and few existing image discrimination models can detect these different types of images. This dissertation discusses a model that can detect different image synthesis techniques, which has good practical application and research value. In addition, we introduce a brand new dataset, TMCface. We use this dataset and other public datasets to compare the performance of baselines with ours. Keywords: Image forensics, Generalization, DeepLearning, ResNet50, TMCface.
URI: https://hdl.handle.net/10356/158878
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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