Image Manipulation Detection Using Augmentation and Convolutional Neural Networks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47942-7_27
Reference10 articles.
1. Hosny, K.M., Mortda, A.M., Fouda, M.M., Lashin, N.A.: An efficient CNN model to detect copy-move image forgery. IEEE Access 10, 48622–48632 (2022). https://doi.org/10.1109/ACCESS.2022.3172273
2. Singh, A., Singh, J.: Image forgery detection using deep neural network. In: 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 504–509 (2021). https://doi.org/10.1109/SPIN52536.2021.9565953
3. Wang, C., Li, Y., Wu, G.: Image splicing tamper detection based on deep learning and attention mechanism. In: 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP), Nanjing, China, pp. 267–271 (2021). https://doi.org/10.1109/ICSIP52628.2021.9688869
4. Barad, Z.J., Goswami, M.M.: Image forgery detection using deep learning: A survey. In: 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, pp. 571–576 (2020). https://doi.org/10.1109/ICACCS48705.2020.9074408
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