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Deep learning
Known as:
DL
, Deep neural networks
, Deep machine learning
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Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set…
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Related topics
Related topics
50 relations
AI takeover
Arithmetic logic unit
Atari
Backpropagation
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Video Description Generation using Audio and Visual Cues
Qin Jin
,
Junwei Liang
International Conference on Multimedia Retrieval
2016
Corpus ID: 7150147
The recent advances in image captioning stimulate the research in generating natural language description for visual content…
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2015
2015
FPGA implementation of a Deep Belief Network architecture for character recognition using stochastic computation
Kayode A. Sanni
,
Guillaume Garreau
,
J. Molin
,
A. Andreou
Annual Conference on Information Sciences and…
2015
Corpus ID: 12843544
Deep Neural Networks (DNNs) have proven very effective for classification and generative tasks, and are widely adapted in a…
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2014
2014
Voice Conversion Based on Speaker-Dependent Restricted Boltzmann Machines
Toru Nakashika
,
T. Takiguchi
,
Y. Ariki
IEICE Trans. Inf. Syst.
2014
Corpus ID: 18710337
SUMMARY This paper presents a voice conversion technique using speaker-dependent Restricted Boltzmann Machines (RBM) to build…
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2014
2014
Cough detection using deep neural networks
Jia-Ming Liu
,
Mingyu You
,
Zheng Wang
,
Guozheng Li
,
Xianghuai Xu
,
Z. Qiu
IEEE International Conference on Bioinformatics…
2014
Corpus ID: 12968635
Cough detection and assessment have crucial clinical value for respiratory diseases. Subjective assessments are widely adopted in…
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2014
2014
Improving deep neural networks for LVCSR using dropout and shrinking structure
Shiliang Zhang
,
Y. Bao
,
Pan Zhou
,
Hui Jiang
,
Lirong Dai
IEEE International Conference on Acoustics…
2014
Corpus ID: 9287367
Recently, the hybrid deep neural networks and hidden Markov models (DNN/HMMs) have achieved dramatic gains over the conventional…
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Highly Cited
2013
Highly Cited
2013
A scalable approach to using DNN-derived features in GMM-HMM based acoustic modeling for LVCSR
Zhijie Yan
,
Qiang Huo
,
Jian Xu
Interspeech
2013
Corpus ID: 530690
We present a new scalable approach to using deep neural network (DNN) derived features in Gaussian mixture density hidden Markov…
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Highly Cited
2013
Highly Cited
2013
Is speech enhancement pre-processing still relevant when using deep neural networks for acoustic modeling?
Marc Delcroix
,
Yotaro Kubo
,
T. Nakatani
,
Atsushi Nakamura
Interspeech
2013
Corpus ID: 40400319
Using deep neural networks (DNNs) for automatic speech recognition (ASR) has recently attracted much attention due to the large…
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2013
2013
Modular combination of deep neural networks for acoustic modeling
Jonas Gehring
,
Wonkyum Lee
,
Kevin Kilgour
,
Ian Lane
,
Yajie Miao
,
A. Waibel
Interspeech
2013
Corpus ID: 6475141
In this work, we propose a modular combination of two popular applications of neural networks to large-vocabulary continuous…
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2012
2012
Inquiry learning is deep learning
B. Bushby
2012
Corpus ID: 155405883
Early years education at Scotch Oakburn College in Launceston, Tasmania, is inspired by the Reggio Emilia Education Project and…
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2006
2006
Three-phase machines and drives-equipment for a laboratory-based course
S. Shirsavar
,
B. Potter
,
I. Ridge
IEEE Transactions on Education
2006
Corpus ID: 38130569
The hazards associated with high-voltage three-phase inverters and high-powered large electrical machines have resulted in most…
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