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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 ...
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 ]
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.
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 ]
A convolutional neural network(CNN) is a regularizedtype of feed-forward neural networkthat learns featuresby itself via filter(or kernel) optimization. This type of deep learningnetwork has been applied to process and make predictions from many different types of data including text, images and audio.[1] Convolution-based networks are the de ...
Adversarial machine learning has other uses besides generative modeling and can be applied to models other than neural networks. In control theory, adversarial learning based on neural networks was used in 2006 to train robust controllers in a game theoretic sense, by alternating the iterations between a minimizer policy, the controller, and a ...