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  2. Audio deepfake - Wikipedia

    en.wikipedia.org/wiki/Audio_deepfake

    Audio deepfake based on imitation is a way of transforming an original speech from one speaker - the original - so that it sounds spoken like another speaker - the target one. [42] An imitation-based algorithm takes a spoken signal as input and alters it by changing its style, intonation, or prosody, trying to mimic the target voice without ...

  3. Deepfake - Wikipedia

    en.wikipedia.org/wiki/Deepfake

    Facebook was the prominent partner in hosting the Deepfake Detection Challenge (DFDC), held December 2019, to 2114 participants who generated more than 35,000 models. [214] The top performing models with the highest detection accuracy were analyzed for similarities and differences; these findings are areas of interest in further research to ...

  4. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  5. Synthetic media - Wikipedia

    en.wikipedia.org/wiki/Synthetic_media

    Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...

  6. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  7. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    There are two markups for Outlier detection (point anomalies) and Changepoint detection (collective anomalies) problems 30+ files (v0.9) CSV Anomaly detection: 2020 (continually updated) [330] [331] Iurii D. Katser and Vyacheslav O. Kozitsin On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study

  8. Copy detection pattern - Wikipedia

    en.wikipedia.org/wiki/Copy_detection_pattern

    A copy detection pattern (CDP) [1] or graphical code [2] [3] is a small random or pseudo-random digital image which is printed on documents, labels or products for counterfeit detection. Authentication is made by scanning the printed CDP using an image scanner or mobile phone camera . [ 4 ]

  9. Data analysis for fraud detection - Wikipedia

    en.wikipedia.org/wiki/Data_analysis_for_fraud...

    Bayesian learning neural network is implemented for credit card fraud detection, telecommunications fraud, auto claim fraud detection, and medical insurance fraud. [ 13 ] Hybrid knowledge/statistical-based systems, where expert knowledge is integrated with statistical power, use a series of data mining techniques for the purpose of detecting ...

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