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Discover LudwigThe phrase "deep learnings" can be used in written English as a noun to refer to the lessons or insights that come from a deep understanding or thorough exploration of a subject
It is often used in the context of learning from experiences or reflections that go beyond surface-level understanding. Example: The project provided me with many deep learnings about the complexities of cross-cultural communication.
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Perhaps a deep learning system to detect deep learning-based image manipulation is just the ticket.
Recently, deep learning-based unsupervised technique of feature learning is adopted that does not require manual intervention.
Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data.
More recently, deep learning-based beamforming methods combined with acoustic modeling were investigated in [11, 12].
We address pose estimation from OCT volume data with a new deep learning-based tracking framework.
Our results are close to those obtained with recent deep learning-based methods.
They're also totally different implementations of deep learning-based image manipulation.
In this paper, we further asses the importance of feature extraction for deep learning-based acoustic event detection.
At Baidu since 2014, Dr. Ng has been working on Deep Speech, a deep learning-based speech recognition system.
We have described two approaches that deal with the importance of feature extraction in deep learning-based AED.
In Section 7, we point out the relation of the presented techniques to deep learning-based architectures.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com