Feb 17, 2017 · In this paper, we adopt a simpler, domain-agnostic approach to dataset augmentation. We start with existing data points and apply simple ...
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By manipulating the vector representation of data within a learned feature space a dataset can be augmented in a number of ways. One of the most basic ...
Feb 17, 2017 · In this work, we demonstrate that extrapolating between samples in feature space can be used to augment datasets and improve the performance of ...
Dataset augmentation, the practice of applying a wide array of domain-specific transformations to synthetically expand a training set, is a standard tool in ...
Dataset augmentation, the practice of applying a wide array of domain-specific transformations to synthetically expand a training set, is a standard tool in ...
Feb 16, 2017 · This paper adopts a simpler, domain-agnostic approach to dataset augmentation, and works in the space of context vectors generated by ...
[PDF] A Closer Look At Feature Space Data Augmentation For Few-Shot Intent ...
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We study six widely different fea- ture space data augmentation methods: 1) up- sampling in the feature space UPSAMPLE, 2) ran- dom perturbation PERTURB, 3) ...
One of the main goals of trajectory transfer is to “fat- ten” a feature space, by augmenting a dataset with feature responses of unseen object poses. In this ...
The problem of data augmentation in feature space is considered. A new architecture, denoted the FeATure TransfEr Network (FATTEN), is proposed for the ...
The proposed data augmentation method can effectively detect defect images whose features include weak features, which improves the integrity of the defect ...
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