Results 31 to 40 of about 24,031,398 (300)
RSMDA: Random Slices Mixing Data Augmentation
Applied Sciences, 2023 Advanced data augmentation techniques have demonstrated great success in deep learning algorithms. Among these techniques, single-image-based data augmentation (SIBDA), in which a single image’s regions are randomly erased in different ways, has shown ...
Teerath Kumar +3 more
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Differentiable Automatic Data Augmentation [PDF]
, 2020 Data augmentation (DA) techniques aim to increase data variability, and thus train deep networks with better generalisation. The pioneering AutoAugment automated the search for optimal DA policies with reinforcement learning. However, AutoAugment is extremely computationally expensive, limiting its wide applicability.
Li, Yonggang +5 more
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Data augmentation approaches for polyp segmentation [PDF]
, 2022 openImage augmentation, and in general data augmentation techniques, can greatly improve the performances of deep neural networks through the creation of artificial patterns, in fact the presence of these new patterns helps the network to generalise thus
DORIZZA, ALBERTO
core
fusion-jena/data-augmentation-ner-legal v1.0.0
, 2022 Source Code for Evaluating Data Augmentation for Named Entity Recognition over the German Legal ...
Erd, Robin, Feddoul, Leila
core +1 more source
Data augmentation with Mobius transformations
Machine Learning: Science and Technology, 2021 Abstract Data augmentation has led to substantial improvements in the performance and generalization of deep models, and remains a highly adaptable method to evolving model architectures and varying amounts of data—in particular, extremely scarce amounts of available training data.
Sharon Zhou +4 more
openaire +2 more sources
data augmentation for chromosomes classification [PDF]
, 2023 openUtilizzo di diversi tipi di data augmentation per ottenere migliori prestazioni durante la classificazione di cromosomi con rete ...
GUGLIELMO, NICOLAS
core
Diffeomorphic transforms for data augmentation [PDF]
, 2022 openL’incremento dei dati è una tecnica ampiamente utilizzata in molti compiti di apprendimento automatico, come la classificazione delle immagini, per ampliare virtualmente la dimensione di dati ed evitare l’overfitting.
COCCO, ALESSIO
core
Spatio-Temporal Data Augmentation for Visual Surveillance
IEEE Access, 2021 Visual surveillance aims to detect a foreground object using a continuous image acquired from a fixed camera. Recent deep learning methods based on supervised learning show superior performance compared to classical background subtraction algorithms ...
Jae-Yeul Kim, Jong-Eun Ha
doaj +1 more source
CoRR, 2015 Dropout is typically interpreted as bagging a large number of models sharing parameters. We show that using dropout in a network can also be interpreted as a kind of data augmentation in the input space without domain knowledge. We present an approach to projecting the dropout noise within a network back into the input space, thereby generating ...
Kishore Reddy Konda +3 more
openaire +3 more sources
PENDUGAAN DATA HILANG DENGAN MENGGUNAKAN DATA AUGMENTATION
Media Statistika, 2011 Data augmentation is a method for estimating missing data. It is a special case of Gibbs sampling which has two important steps. The first step is imputation or I-step where the missing data is generated based on the conditional distributions for missing
Mesra Nova, Moch. Abdul Mukid
doaj +1 more source