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Autoencoder
Known as:
Autoassociator
, Diabolo network
, Auto-encoder
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An autoencoder, autoassociator or Diabolo network is an artificial neural network used for unsupervised learning of efficient codings.The aim of an…
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Related topics
Related topics
32 relations
Activation function
Artificial neural network
Backpropagation
Conjugate gradient method
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
An Online Writer Identification System based on Beta-Elliptic Model and Fuzzy Elementary Perceptual Codes
Thameur Dhieb
,
S. Njah
,
H. Boubaker
,
W. Ouarda
,
Mounir Ben Ayed
,
A. Alimi
arXiv.org
2018
Corpus ID: 4892524
Actually, the ability to identify the documents authors provides more chances for using these documents for various purposes. In…
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2017
2017
A Semi-Supervised Predictive Sparse Decomposition Based on Task-Driven Dictionary Learning
Le Lv
,
Dongbin Zhao
,
Qingqiong Deng
Cognitive Computation
2017
Corpus ID: 5877546
In feature learning field, many methods are inspired by advances in neuroscience. Among them, neural network and sparse coding…
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2017
2017
Location deployment of depots and resource relocation for connected car-sharing systems through mobile edge computing
Xiaolu Zhu
,
Jinglin Li
,
Zhihan Liu
,
Fangchun Yang
Int. J. Distributed Sens. Networks
2017
Corpus ID: 20971264
Mobile edge computing supports the connected cars to ensure real-time, interactive, secured, and distributed services for…
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2017
2017
Combining local and global: Rich and robust feature pooling for visual recognition
Wei Xiong
,
Lefei Zhang
,
Bo Du
,
D. Tao
Pattern Recognition
2017
Corpus ID: 9810778
2016
2016
A Promising Non-invasive CAD System for Kidney Function Assessment
M. Shehata
,
F. Khalifa
,
+5 authors
A. El-Baz
International Conference on Medical Image…
2016
Corpus ID: 26695742
This paper introduces a novel computer-aided diagnostic (CAD) system for the assessment of renal transplant status that…
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2015
2015
Three ways to adapt a CTS recognizer to unseen reverberated speech in BUT system for the ASpIRE challenge
M. Karafiát
,
F. Grézl
,
L. Burget
,
Igor Szöke
,
J. Černocký
Interspeech
2015
Corpus ID: 36708585
This paper describes several strategies tested in BUT’s sub-mission to the IARPA ASpIRE challenge. The ASpIRE task was to develop…
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2007
2007
Condition Monitoring of HV Bushings in the Presence of Missing Data Using Evolutionary Computing
S. M. Dhlamini
,
F. Nelwamondo
,
T. Marwala
arXiv.org
2007
Corpus ID: 57269
The work proposes the application of neural networks with particle swarm optimisation (PSO) and genetic algorithms (GA) to…
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Highly Cited
2001
Highly Cited
2001
A nonlinear neural network model of mixture of local principal component analysis: application to handwritten digits recognition
Bailing Zhang
,
M. Fu
,
Hong Yan
Pattern Recognition
2001
Corpus ID: 2500168
1995
1995
A system for data extraction from forms of known class
F. Cesarini
,
M. Gori
,
S. Marinai
,
G. Soda
Proceedings of the International Conference on…
1995
Corpus ID: 46543752
In this paper, we describe a flexible and efficient system for processing forms of a known class. The model is based on…
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Highly Cited
1990
Highly Cited
1990
Extracting features from faces using compression networks: Face
G. Cottrell
1990
Corpus ID: 59906275
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