• U-Net

  • Referenced in 71 articles [sw33176]
  • relies on the strong use of data augmentation to use the available annotated samples more...
  • BayesLogit

  • Referenced in 44 articles [sw09312]
  • latent variables. We propose a new data-augmentation strategy for fully Bayesian inference in models ... count data. In each case, our data-augmentation strategy leads to simple, effective methods ... Hastings; and (2) outperform other known data-augmentation strategies, both in ease...
  • Monomvn

  • Referenced in 11 articles [sw08173]
  • scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness...
  • MNP

  • Referenced in 8 articles [sw10537]
  • based on the efficient marginal data augmentation algorithm that is developed by Imai...
  • bnlearn

  • Referenced in 65 articles [sw08265]
  • tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented ... utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced...
  • Augmentor

  • Referenced in 3 articles [sw28298]
  • Image Augmentation Library for Machine Learning. The generation of artificial data ... based on existing observations, known as data augmentation, is a technique used in machine learning ... level API for the expansion of image data using a stochastic, pipeline-based approach which ... sampled from a distribution of augmented images at runtime. Augmentor provides methods for most standard...
  • SpecAugment

  • Referenced in 2 articles [sw37168]
  • SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition. We present SpecAugment, a simple ... data augmentation method for speech recognition. SpecAugment is applied directly to the feature inputs...
  • batchgenerators

  • Referenced in 3 articles [sw32333]
  • suit all our deep learning data augmentation needs. It is not (yet) perfect...
  • DENSER

  • Referenced in 3 articles [sw34794]
  • tunes hyper-parameters (e.g., learning or data augmentation parameters). The automatic design is achieved using...
  • DropEdge

  • Referenced in 3 articles [sw37753]
  • each training epoch, acting like a data augmenter and also a message passing reducer. Furthermore...
  • V-Net

  • Referenced in 5 articles [sw35860]
  • process 2D images while most medical data used in clinical practice consists of 3D volumes ... annotated volumes available for training, we augment the data applying random non-linear transformations...
  • Audiogmenter

  • Referenced in 1 article [sw34920]
  • Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation. Audio data augmentation is a key step ... introduce Audiogmenter, a novel audio data augmentation library in MATLAB. We provide 15 different augmentation ... audio data and 8 for spectrograms. We efficiently implemented several augmentation techniques whose usefulness ... this is the largest MATLAB audio data augmentation library freely available. We validate the efficiency...
  • AutoAugment

  • Referenced in 1 article [sw39069]
  • AutoAugment: Learning Augmentation Policies from Data. Data augmentation is an effective technique for improving ... modern image classifiers. However, current data augmentation implementations are manually designed. In this paper ... AutoAugment to automatically search for improved data augmentation policies. In our implementation, we have designed ... CIFAR-100, SVHN, and ImageNet (without additional data). On ImageNet, we attain...
  • MDI

  • Referenced in 2 articles [sw35028]
  • least squares regression algorithm (NIPALS) and data augmentation (DA). MDI Toolbox presents a general procedure...
  • inorm

  • Referenced in 2 articles [sw24701]
  • using the EM algorithm and a data augmentation MCMC). By default it uses a Windows...
  • muda

  • Referenced in 1 article [sw34923]
  • muda: A library for Musical Data Augmentation. muda package implements annotation-aware musical data augmentation ... consistently apply perturbations to annotated music data for the purpose of fitting statistical models...
  • iNLTK

  • Referenced in 1 article [sw39138]
  • support for Data Augmentation, Textual Similarity, Sentence Embeddings, Word Embeddings, Tokenization and Text Generation ... using pre-trained models and data augmentation from iNLTK, we can achieve more than ... using less than 10% of the training data. iNLTK is already being widely used...
  • DeepSentiPers

  • Referenced in 1 article [sw32537]
  • Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus. This paper focuses ... architectures need to feed on big annotated data as well as an accurate design ... both cases. Second, we suggested three data augmentation techniques for the low-resources Persian sentiment ... word embedding methods show that our data augmentation methods and intended models successfully address...
  • binomlogit

  • Referenced in 1 article [sw36816]
  • model within a Bayesian framework: a data-augmented independence MH-sampler, an auxiliary mixture sampler ... procedures are based on algorithms using data augmentation, where the regression coefficients are estimated...
  • Albumentations

  • Referenced in 1 article [sw32338]
  • Albumentations: fast and flexible image augmentations. Data augmentation is a commonly used technique for increasing...