Results 181 to 190 of about 9,759,453 (201)

The Method of Augmented Sampling

Applied Statistics, 1968
In this paper we present a new sampling scheme called the method of augmented sampling. The scheme is essentially a two sample procedure and is useful in surveys where all except one of the variates are similarly distributed and the distribution of the single variate differs markedly from the others.
openaire   +1 more source

Sample Augmentation for Classification of Schizophrenia Patients and Healthy Controls Using ICA of fMRI Data and Convolutional Neural Networks

International Conference on Intelligent Control and Information Processing, 2019
Convolutional neural networks (CNN) have exhibited great success in image classification. The application of CNN to classification of patients with brain disorders and healthy controls is also promising using functional magnetic resonance imaging (fMRI ...
Yan-Wei Niu, Qiuhua Lin, Yue Qiu, Li-Dan Kuang, V. Calhoun   +4 more
semanticscholar   +1 more source

Augmented Leverage Score Sampling with Bounds

2016
We introduce a modification to the well studied leverage score sampling algorithm which takes into account data scale, called the augmented leverage score, and introduce an initial error bound proof for the case of deterministic sampling – which to our knowledge is the first bound for this augmented leverage score.
Daniel J. Perry, Ross T. Whitaker
openaire   +1 more source

SelectAugment: Hierarchical Deterministic Sample Selection for Data Augmentation

Proceedings of the AAAI Conference on Artificial Intelligence, 2023
Data augmentation (DA) has been extensively studied to facilitate model optimization in many tasks. Prior DA works focus on designing augmentation operations themselves, while leaving selecting suitable samples for augmentation out of consideration. This might incur visual ambiguities and further induce training biases.
Shiqi Lin, Zhizheng Zhang, Xin Li, Zhibo Chen   +3 more
openaire   +1 more source

Extended Communication Samples of Augmented Communicators II

Journal of Speech and Hearing Disorders, 1990
The three primary purposes of this project are (a) to identify those word sequences that occur frequently across a group of 10 linguistically intact augmented communicators, (b) to determine the communality with which the various augmented communicators use specific word sequences, and (c) to evaluate the usefulness of word sequences in providing ...
K M, Yorkston, D R, Beukelman, K, Smith, R, Tice   +3 more
openaire   +2 more sources

Artificially Augmented Samples, Shrinkage, and Mean Squared Error Reduction*

Journal of the American Statistical Association, 2005
An inequality is provided that determines when shrinkage reduces the mean squared error (MSE) of an unbiased estimate. Artificially augmented samples are then used to obtain, among others, shrinkage estimates of the population's variance and covariance, which improve the unbiased estimates for all parameter values and for all probability models with ...
openaire   +3 more sources

Prototype Augmentation with Dummy Samples

2022 26th International Conference on Pattern Recognition (ICPR), 2022
Hong Yu, Fanzhang Li
openaire   +1 more source

WGAN-CL: A Wasserstein GAN with confidence loss for small-sample augmentation

Expert systems with applications, 2023
Jiaqi Mi, Congcong Ma, Lihua Zheng, Man Zhang, Minzan Li, Minjuan Wang   +5 more
semanticscholar   +1 more source

Iterative Spatial-Spectral Training Sample Augmentation for Effective Hyperspectral Image Classification

IEEE Geoscience and Remote Sensing Letters, 2022
Xiaodi Shang, Sichao Han, Meiping Song
semanticscholar   +1 more source

Electricity theft detection in unbalanced sample distribution: a novel approach including a mechanism of sample augmentation

Applied intelligence (Boston), 2022
Ruizhe Yao, Ning Wang, Weipeng Ke, Peng Chen, X. Sheng   +4 more
semanticscholar   +1 more source