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Crowdsourcing-based multimedia subjective evaluations: a case study on image recognizability and aesthetic appeal.

, , , , , and . CrowdMM@ACM Multimedia, page 29-34. ACM, (2013)

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Custom Attribution Loss for Improving Generalization and Interpretability of Deepfake Detection., , and . ICASSP, page 8972-8976. IEEE, (2022)DeepFakes: a New Threat to Face Recognition? Assessment and Detection., and . CoRR, (2018)Best practices and recommendations for crowdsourced qoe, , , , , , , , , and . Qualinet White Paper, (2014)Vulnerability of Face Recognition to Deep Morphing., and . CoRR, (2019)Quality evaluation of HEVC and VP9 video compression in real-time applications., , , and . QoMEX, page 1-6. IEEE, (2015)Subjective quality assessment database of HDR images compressed with JPEG XT., , , , , and . QoMEX, page 1-6. IEEE, (2015)On the use of convolutional neural networks for speech presentation attack detection., , , , and . ISBA, page 1-8. IEEE, (2018)Impact of Tone-mapping Algorithms on Subjective and Objective Face Recognition in HDR Images., , , and . CrowdMM@ACM Multimedia, page 39-44. ACM, (2015)Crowdsourcing-based multimedia subjective evaluations: a case study on image recognizability and aesthetic appeal., , , , , and . CrowdMM@ACM Multimedia, page 29-34. ACM, (2013)ADGD'21: 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection., , , and . ACM Multimedia, page 5698-5699. ACM, (2021)