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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 cellular clone fraud. Specifically, a rule-learning program to uncover indicators of fraudulent behaviour from a large database of customer transactions is implemented.
In order to assess the most effective algorithms for detecting deepfakes, a coalition of leading technology companies hosted the Deepfake Detection Challenge to accelerate the technology for identifying manipulated content. [173] The winning model of the Deepfake Detection Challenge was 65% accurate on the holdout set of 4,000 videos. [174]
For this reason, many researchers have suggested following a self-supervised learning approach, [59] dealing with unlabeled data to work effectively in detection tasks and improving the model's scalability, and, at the same time, decreasing the computational cost. Training and testing models with real audio data is still an underdeveloped area.
The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [395] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [396] University of Zurich GreenBiz
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 ...
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.
Hugging Face, Inc. is an American company incorporated under the Delaware General Corporation Law [1] and based in New York City that develops computation tools for building applications using machine 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 ...