Review on deep learning applications in frequency analysis and control of modern power system
The penetration of renewable energy resources (RES) generation and the interconnection of
regional power grids in wide area and large scale have led the modern power system to …
regional power grids in wide area and large scale have led the modern power system to …
A tutorial survey of architectures, algorithms, and applications for deep learning
L Deng - APSIPA transactions on Signal and Information …, 2014 - cambridge.org
In this invited paper, my overview material on the same topic as presented in the plenary
overview session of APSIPA-2011 and the tutorial material presented in the same …
overview session of APSIPA-2011 and the tutorial material presented in the same …
[引用][C] The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence
K Crawford - 2021 - books.google.com
The hidden costs of artificial intelligence, from natural resources and labor to privacy and
freedom What happens when artificial intelligence saturates political life and depletes the …
freedom What happens when artificial intelligence saturates political life and depletes the …
A survey of deep neural network architectures and their applications
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep
learning techniques have drawn ever-increasing research interests because of their …
learning techniques have drawn ever-increasing research interests because of their …
Deep learning: methods and applications
This monograph provides an overview of general deep learning methodology and its
applications to a variety of signal and information processing tasks. The application areas …
applications to a variety of signal and information processing tasks. The application areas …
An analysis of environment, microphone and data simulation mismatches in robust speech recognition
Speech enhancement and automatic speech recognition (ASR) are most often evaluated in
matched (or multi-condition) settings where the acoustic conditions of the training data …
matched (or multi-condition) settings where the acoustic conditions of the training data …
Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
Most current speech recognition systems use hidden Markov models (HMMs) to deal with
the temporal variability of speech and Gaussian mixture models (GMMs) to determine how …
the temporal variability of speech and Gaussian mixture models (GMMs) to determine how …
Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition
We propose a novel context-dependent (CD) model for large-vocabulary speech recognition
(LVSR) that leverages recent advances in using deep belief networks for phone recognition …
(LVSR) that leverages recent advances in using deep belief networks for phone recognition …
Machine learning paradigms for speech recognition: An overview
L Deng, X Li - IEEE Transactions on Audio, Speech, and …, 2013 - ieeexplore.ieee.org
Automatic Speech Recognition (ASR) has historically been a driving force behind many
machine learning (ML) techniques, including the ubiquitously used hidden Markov model …
machine learning (ML) techniques, including the ubiquitously used hidden Markov model …