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Found 5 papers, 3 papers with code
Astronomical image time series classification using CONVolutional attENTION (ConvEntion)
In this work, we solved various problems the datasets tend to suffer from and we present new results for classifications using astronomical image time series with an increase in accuracy of 13%, compared to state-of-the-art approaches that use image time series, and a 12% increase, compared to approaches that use light curves.
A study on the invariance in security whatever the dimension of images for the steganalysis by deep-learning
In this paper, we study the performance invariance of convolutional neural networks when confronted with variable image sizes in the context of a more "wild steganalysis".
LSSD: a Controlled Large JPEG Image Database for Deep-Learning-based Steganalysis "into the Wild"
In this paper, we describe a large JPEG database composed of 2 million colour and grey-scale images.
Cryptography and Security
A CNN adapted to time series for the classification of Supernovae
The first one is adapted to time series and thus to the treatment of supernovae light-curves.
How to augment a small learning set for improving the performances of a CNN-based steganalyzer?
To our knowledge, no study has been performed on the enrichment impact of a learning database on the steganalysis performance.
