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Rprop
Known as:
Resilient backpropagation
, Resilient propagation
Rprop, short for resilient backpropagation, is a learning heuristic for supervised learning in feedforward artificial neural networks. This is a…
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Related topics
Related topics
11 relations
Algorithm
Artificial neural network
Backpropagation
Deep learning
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
International Journal of Swarm Intelligence and Evolutionary Computation
JP Kelwade
,
Bapurao
,
S. Salankar
2017
Corpus ID: 44822144
The study of Heart rate variability is recently gained momentum for an estimation of heart health. This paper suggests a new…
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2015
2015
Enhanced Image Steganography System based on Discrete Wavelet Transformation and Resilient Back-Propagation
R. Naoum
,
A. Shihab
,
S. AlHamouz
2015
Corpus ID: 212580654
Summary Image hiding is a form of steganography that works by embedding data into a digital media for the purpose of…
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2008
2008
Estimating landmark locations from geo-referenced photographs
Henrik Kretzschmar
,
C. Stachniss
,
Christian Plagemann
,
Wolfram Burgard
IEEE/RSJ International Conference on Intelligent…
2008
Corpus ID: 2725916
The problem of estimating the positions of landmarks using a mobile robot equipped with a camera has intensively been studied in…
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2008
2008
Grain classification using hierarchical clustering and self-adaptive neural network
Chen Xiao
,
Chen Tao
,
X. Yi
,
Wei Li
,
Tan Yuzhi
World Congress on Intelligent Control and…
2008
Corpus ID: 15329154
Self-adaptive back propagation neural network (BPNN) models based on hierarchical clustering were developed to classify corn…
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2002
2002
Application of neural network techniques for location predication in mobile networking
Pradeep Bilurkar
,
N. Rao
,
G. Krishna
,
Ravi Jain
Proceedings of the 9th International Conference…
2002
Corpus ID: 61041728
Over the last few years, the worldwide cellular communication market has undergone exponential growth. This can be attributed to…
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2002
2002
An integrated algorithm of magnified gradient function and weight evolution for solving local minima problem
S. Ng
,
S. Leung
,
A. Luk
Proceedings of the International Joint…
2002
Corpus ID: 124740920
This paper presents the integration of magnified gradient function and weight evolution algorithms in order to solve the local…
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1997
1997
Urban land use mapping with multi-spectral and SAR satellite data using neural networks
Jukka Heikkonen
,
I. Kanellopoulos
,
Aristide Varfis3
,
A. Steel
,
Karen Fullerton2
IGARSS'97. IEEE International Geoscience and…
1997
Corpus ID: 61287734
Statistical, textural and Gabor features were extracted from integrated multitemporal multispectral TM data and ERS-1 SAR imagery…
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1997
1997
A Cascade Network Algorithm Employing Progressive RPROP
N. Treadgold
,
Tom Gedeon
International Work-Conference on Artificial and…
1997
Corpus ID: 11722095
Cascade Correlation (Cascor) has proved to be a powerful method for training neural networks. Cascor, however, has been shown not…
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1997
1997
Computational neural networks for mapping calorimetric data: Application of feed-forward neural networks to kinetic parameters determination and signals filtering
N. Sbirrazzuoli
,
D. Brunnel
Neural computing & applications (Print)
1997
Corpus ID: 24157712
Feedforward neural networks have been used for kinetic parameters determination and signal filtering in differential scanning…
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1997
1997
Adaptation of Learning Rule Parameters Using a Meta Neural Network
Colin McCormack
Connection science
1997
Corpus ID: 9798679
This paper proposes an application-independent method of automating learning rule parameter selection using a form of supervisor…
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