Search results
Results from the WOW.Com Content Network
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 ...
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.
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.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
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 ...
ImageNet. The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [ 1 ][ 2 ] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [ 3 ]
The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. [ 1 ][ 2 ] The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. [ 3 ]
LabelMe. LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) that provides a dataset of digital images with annotations. The dataset is dynamic, free to use, and open to public contribution. The most applicable use of LabelMe is in computer vision research.