Results 11 to 20 of about 4,502,013 (256)

Improving Photometric Redshift Estimates with Training Sample Augmentation

The Astrophysical Journal Letters
Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy
Irene Moskowitz, Eric Gawiser, John Franklin Crenshaw, Brett H. Andrews, Alex I. Malz, Samuel Schmidt, The LSST Dark Energy Science Collaboration   +6 more
doaj   +2 more sources

Cooperative Augmentation of Smart Objects with Projector-Camera Systems [PDF]

, 2007
In this paper we present a new approach for cooperation between mobile smart objects and projector-camera systems to enable augmentation of the surface of objects with interactive projected displays.
Molyneaux, David, Kortuem, G., Gellersen, H., Kortuem, Gerd, Gellersen, Hans, Schiele, B. ; https://orcid.org/, Schiele, Bernt, Molyneaux, D.   +7 more
core   +5 more sources

Bayesian Analysis of Sample Selection and Endogenous Switching Regression Models with Random Coefficients Via MCMC Methods [PDF]

, 2002
This paper develops a Bayesian method for estimating and testing the parameters of the endogenous switching regression model and sample selection models.
Odejar, M. A. E.
core   +1 more source

Constrained sample augmentation.

, 2023
Hypothetical sampling procedure in which an initial sample of N = 8 is incremented by 4, only if 0.05≤pN = 32. (a) Distribution of initial p values (dark blue) vs. final “p values” (pale blue) in simulations with no real effect.
Pamela Reinagel (282995)
core   +1 more source

MetaAugment: Sample-Aware Data Augmentation Policy Learning

, 2021
Automated data augmentation has shown superior performance in image recognition. Existing works search for dataset-level augmentation policies without considering individual sample variations, which are likely to be sub-optimal.
Xie, Chuanlong, Zhou, Fengwei, Chen, Fei, Li, Zhenguo, Hong, Lanqing, Li, Jiawei, Sun, Rui   +6 more
core   +1 more source

zeshankhan/Augmentation: V1.0

, 2023
The augmentation of the images using various types of flips, rotates, crops and ...
Zeshan Khan
core   +1 more source

A GAN-Based Augmentation Scheme for SAR Deceptive Jamming Templates with Shadows

Remote Sensing, 2023
To realize fast and effective synthetic aperture radar (SAR) deception jamming, a high-quality SAR deception jamming template library can be generated by performing sample augmentation on SAR deception jamming templates.
Shinan Lang, Guiqiang Li, Yi Liu, Wei Lu, Qunying Zhang, Kun Chao   +5 more
doaj   +1 more source

Variational Autoencoders for Data Augmentation in Clinical Studies

Applied Sciences, 2023
Sample size estimation is critical in clinical trials. A sample of adequate size can provide insights into a given population, but the collection of substantial amounts of data is costly and time-intensive.
Dimitris Papadopoulos, Vangelis D. Karalis   +1 more
doaj   +1 more source

A Rolling Bearing Fault Diagnosis Based on Conditional Depth Convolution Countermeasure Generation Networks under Small Samples

Sensors, 2022
Aiming at the problems of low fault diagnosis accuracy caused by insufficient samples and unbalanced data sample distribution in bearing fault diagnosis, this paper proposes a fault diagnosis method for rolling bearings referencing conditional deep ...
Cheng Peng, Shuting Zhang, Changyun Li
doaj   +1 more source

Dynamic Data Augmentation Method for Hyperspectral Image Classification Based on Siamese Structure

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
At present, deep learning classification researches of hyperspectral usually focus on optimizing the classification model. In essence, most of them did not take special measures for the characteristics of the small sample and imbalanced category ...
Hongmin Gao, Junpeng Zhang, Xueying Cao, Zhonghao Chen, Yiyan Zhang, Chenming Li   +5 more
doaj   +1 more source