Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods
Summary
Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods is a scholarly article[1].
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Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods. Retrieved May 24, 2026, from https://4ort.xyz/entity/deepfake-forensics-cross-manipulation-robustness-of-feedforward-and-recurrent-convolutional-forgery-detection-methods
MLA“Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deepfake-forensics-cross-manipulation-robustness-of-feedforward-and-recurrent-convolutional-forgery-detection-methods.
BibTeX@misc{4ortxyz_deepfake-forensics-cross-manipulation-robustness-of-feedforward-and-recurrent-convolutional-forgery-detection-methods_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods}}, year = {2026}, url = {https://4ort.xyz/entity/deepfake-forensics-cross-manipulation-robustness-of-feedforward-and-recurrent-convolutional-forgery-detection-methods}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods — https://4ort.xyz/entity/deepfake-forensics-cross-manipulation-robustness-of-feedforward-and-recurrent-convolutional-forgery-detection-methods (retrieved 2026-05-24)