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These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high ...
Contents. List of datasets in computer vision and image processing. This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research. These datasets consist primarily of images or videos for tasks such as object detection, facial recognition, and multi-label classification.
zenodo.org. Zenodo is a general-purpose open repository developed under the European OpenAIRE program and operated by CERN. [1][2][3] It allows researchers to deposit research papers, data sets, research software, reports, and any other research related digital artefacts. For each submission, a persistent digital object identifier (DOI) is ...
MNIST database. The MNIST database (Modified National Institute of Standards and Technology database[ 1 ]) is a large database of handwritten digits that is commonly used for training various image processing systems. [ 2 ][ 3 ] The database is also widely used for training and testing in the field of machine learning. [ 4 ][ 5 ] It was created ...
Anna Kreshuk. Anna Kreshuk is a group leader at the European Molecular Biology Laboratory in Heidelberg, Germany. She joined the Cell Biology and Biophysics Unit in July 2018, where her group employs machine learning to develop automated methods to help biologists speed up image analysis. [1][2]
Training, validation, and test data sets. In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. [ 1 ] Such algorithms function by making data-driven predictions or decisions, [ 2 ] through building a mathematical model from input data.
v. t. e. Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
Yoshua Bengio OC FRS FRSC (born March 5, 1964 [3]) is a Canadian computer scientist, most noted for his work on artificial neural networks and deep learning. [4] [5] [6] He is a professor at the Department of Computer Science and Operations Research at the Université de Montréal and scientific director of the Montreal Institute for Learning Algorithms (MILA).