• U-Net

  • Referenced in 94 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 12 articles [sw08173]
  • scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness...
  • BayesEstDiffusion.jl

  • Referenced in 7 articles [sw40280]
  • chain Monte-Carlo method known as data-augmentation. If unknown parameters appear in the diffusion ... coefficient, direct implementation of data-augmentation results in a Markov chain that is reducible. Furthermore ... data-augmentation requires efficient sampling of diffusion bridges, which can be difficult, especially...
  • MNP

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

  • Referenced in 4 articles [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...
  • bnlearn

  • Referenced in 68 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...
  • batchgenerators

  • Referenced in 4 articles [sw32333]
  • suit all our deep learning data augmentation needs. It is not (yet) perfect...
  • V-Net

  • Referenced in 6 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...
  • 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...
  • DENSER

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

  • Referenced in 3 articles [sw39131]
  • other end-to-end systems without data augmentation, and is 4--11x faster...
  • DropEdge

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

  • Referenced in 1 article [sw40532]
  • RandAugment: Practical automated data augmentation with a reduced search space. Recent work has shown that ... data augmentation has the potential to significantly improve the generalization of deep learning models. Recently ... leads to 1.0-1.3% improvement over baseline augmentation, and is within 0.3% mAP of AutoAugment ... used to investigate the role of data augmentation with varying model and dataset size. Code...
  • MDI

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

  • Referenced in 2 articles [sw40838]
  • Approach for Clinical Trials. Functions for data augmentation using the Bayesian discount prior method...
  • inorm

  • Referenced in 2 articles [sw24701]
  • using the EM algorithm and a data augmentation MCMC). By default it uses a Windows...
  • YOLOv4

  • Referenced in 2 articles [sw40822]
  • CmBN, SAT, Mish activation, Mosaic data augmentation, CmBN, DropBlock regularization, and CIoU loss, and combine...