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A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .
OpenML: [494] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [495] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [7] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [5]
Pioneering machine learning research is conducted using simple algorithms. 1960s: Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s
Knowledge discovery is an iterative and interactive process used to identify, analyze and visualize patterns in data. [1] Network analysis, link analysis and social network analysis are all methods of knowledge discovery, each a corresponding subset of the prior method.
Hideto Tomabechi (苫米地 英人, Tomabechi Hideto, born 1959) (PhD, professor, adjunct fellow) (Knight: Cav. di Gr. Cr.) [1] is a Japanese cognitive scientist (computational linguistics, functional brain science, cognitive psychology, cognitive warfare, analytic philosophy) computer scientist (distributed processing, discrete mathematics, artificial intelligence, cyber security).
Machine vision is a series of algorithms, or mathematical procedures, which work like a flow-chart or series of questions to compare the object seen with hundreds of thousands of stored reference images of humans in different postures, angles, positions and movements. The A.I. asks itself if the observed object moves like the reference images ...
Anomaly detection has become increasingly vital in video surveillance to enhance security and safety. [ 13 ] [ 14 ] With the advent of deep learning technologies, methods using Convolutional Neural Networks (CNNs) and Simple Recurrent Units (SRUs) have shown significant promise in identifying unusual activities or behaviors in video data. [ 13 ]