Volume 3, Issue 3 (September, 2022) – 2 articles
Cover Picture: Deep learning is very successful in computer vision, e.g., object detection, image classification, but these tasks can be easily perceived by human beings. However, it is incapable for human eyes to distinguish forged images from untouched ones. To investigate the performance in detecting seam-carving-based image forgery with popular deep learning models that were used in image forensics, including image steganalysis and image forgery detection, several deep learning models were compared, and the study shows that EfficientNet performs the best, followed by SRnet and LFnet. The current study also demonstrates that the different optimizers led to different detection testing accuracy with the Efficientnet-B5. In the experiments, AdamW is generally superior to Adam and SGD. The current study also indicates that deep learning is very promising in image forensics that is hardly discernable to human perceptions.
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