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Sample images from MNIST test dataset. 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 ...
The Fashion MNIST dataset is a large freely available database of fashion images that is commonly used for training and testing various machine learning systems. [1] [2] Fashion-MNIST was intended to serve as a replacement for the original MNIST database for benchmarking machine learning algorithms, as it shares the same image size, data format and the structure of training and testing splits.
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 ...
LeNet-5 architecture (detailed). LeNet is a series of convolutional neural network structure proposed by LeCun et al.. [ 1 ] The earliest version, LeNet-1, was trained in 1989. In general, when "LeNet" is referred to without a number, it refers to LeNet-5 (1998), the most well-known version.
FieldSAFE. Multi-modal dataset for obstacle detection in agriculture including stereo camera, thermal camera, web camera, 360-degree camera, lidar, radar, and precise localization. Classes labelled geographically. >400 GB of data. Images and 3D point clouds. Classification, object detection, object localization. 2017.
CIFAR-10 is a set of images that can be used to teach a computer how to recognize objects. Since the images in CIFAR-10 are low-resolution (32x32), this dataset can allow researchers to quickly try different algorithms to see what works. CIFAR-10 is a labeled subset of the 80 Million Tiny Images dataset from 2008, published in 2009.
Talk. : MNIST database. This is the talk page for discussing improvements to the MNIST database article. This is not a forum for general discussion of the article's subject. Assume good faith. Be polite and avoid personal attacks. Be welcoming to newcomers. Seek dispute resolution if needed.
e. t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map. It is based on Stochastic Neighbor Embedding originally developed by Geoffrey Hinton and Sam Roweis, [1] where Laurens van der Maaten and Hinton proposed the ...