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28 relations: Academic publishing, Affine transformation, Americans, Caltech 101, Computer performance, Conference on Computer Vision and Pattern Recognition, Convolutional neural network, Data pre-processing, Database, Deformation (engineering), Digital image processing, Gradient boosting, Haar-like feature, Institute of Electrical and Electronics Engineers, K-nearest neighbors algorithm, LabelMe, Linear classifier, Linear discriminant analysis, List of datasets for machine learning research, Machine learning, National Institute of Standards and Technology, Neural network, Normalization (image processing), Secondary school, Spatial anti-aliasing, Support vector machine, Training, test, and validation sets, United States Census Bureau.
Academic publishing
Academic publishing is the subfield of publishing which distributes academic research and scholarship.
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Affine transformation
In geometry, an affine transformation, affine mapBerger, Marcel (1987), p. 38.
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Americans
Americans are citizens of the United States of America.
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Caltech 101
Caltech 101 is a data set of digital images created in September 2003 and compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro Perona at the California Institute of Technology.
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Computer performance
Computer performance is the amount of work accomplished by a computer system.
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Conference on Computer Vision and Pattern Recognition
The Conference on Computer Vision and Pattern Recognition is an annual conference on computer vision and pattern recognition, by several measures regarded as the top conference in computer vision.
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Convolutional neural network
In machine learning, a convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural networks, most commonly applied to analyzing visual imagery.
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Data pre-processing
Data pre-processing is an important step in the data mining process.
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Database
A database is an organized collection of data, stored and accessed electronically.
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Deformation (engineering)
In materials science, deformation refers to any changes in the shape or size of an object due to-.
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Digital image processing
In computer science, Digital image processing is the use of computer algorithms to perform image processing on digital images.
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Gradient boosting
Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees.
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Haar-like feature
Haar-like features are digital image features used in object recognition.
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Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers (IEEE) is a professional association with its corporate office in New York City and its operations center in Piscataway, New Jersey.
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K-nearest neighbors algorithm
In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.
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LabelMe
LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) which provides a dataset of digital images with annotations.
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Linear classifier
In the field of machine learning, the goal of statistical classification is to use an object's characteristics to identify which class (or group) it belongs to.
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Linear discriminant analysis
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events.
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List of datasets for machine learning research
These datasets are used for machine-learning research and have been cited in peer-reviewed academic journals.
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Machine learning
Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
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National Institute of Standards and Technology
The National Institute of Standards and Technology (NIST) is one of the oldest physical science laboratories in the United States.
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Neural network
The term neural network was traditionally used to refer to a network or circuit of neurons.
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Normalization (image processing)
In image processing, normalization is a process that changes the range of pixel intensity values.
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Secondary school
A secondary school is both an organization that provides secondary education and the building where this takes place.
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Spatial anti-aliasing
In digital signal processing, spatial anti-aliasing is the technique of minimizing the distortion artifacts known as aliasing when representing a high-resolution image at a lower resolution.
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Support vector machine
In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
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Training, test, and validation sets
In machine learning, the study and construction of algorithms that can learn from and make predictions on data is a common task.
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United States Census Bureau
The United States Census Bureau (USCB; officially the Bureau of the Census, as defined in Title) is a principal agency of the U.S. Federal Statistical System, responsible for producing data about the American people and economy.
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MNIST, MNIST dataset, Mixed National Institute of Standards and Technology database.
References
[1] https://en.wikipedia.org/wiki/MNIST_database
