-
1
-
-
84902184683
-
Mitochondrial dysfunction as a neurobiological subtype of autism spectrum disorder: Evidence from brain imaging
-
Goh, S., et al., “Mitochondrial dysfunction as a neurobiological subtype of autism spectrum disorder: Evidence from brain imaging,” JAMA Psychiatry, Vol. 71, No. 6, 665-671, 2014.
-
(2014)
JAMA Psychiatry
, vol.71
, Issue.6
, pp. 665-671
-
-
Goh, S.1
-
2
-
-
84885597453
-
An MR brain images classifier system via particle swarm optimization and kernel support vector machine
-
Zhang, Y., et al., “An MR brain images classifier system via particle swarm optimization and kernel support vector machine,” The Scientific World Journal, Vol. 2013, 9, 2013.
-
(2013)
The Scientific World Journal
, vol.2013
, pp. 9
-
-
Zhang, Y.1
-
3
-
-
58149512473
-
Second order fuzzy measure and weighted co-occurrence matrix for segmentation of brain MR images
-
Maji, P., M. K. Kundu, and B. Chanda, “Second order fuzzy measure and weighted co-occurrence matrix for segmentation of brain MR images,” Fundamenta Informaticae, Vol. 88, Nos. 12, 161-176, 2008.
-
(2008)
Fundamenta Informaticae
, vol.88
, Issue.12
, pp. 161-176
-
-
Maji, P.1
Kundu, M.K.2
Chanda, B.3
-
4
-
-
84897116509
-
Brain tumor detection and segmentation in a CRF (Conditional random fields) framework with pixel-pairwise affinity and superpixel-level features
-
Wu, W., et al., “Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features,” International Journal of Computer Assisted Radiology and Surgery, Vol. 9, No. 2, 241-253, Mar. 2014.
-
(2014)
International Journal of Computer Assisted Radiology and Surgery
, vol.9
, Issue.2
, pp. 241-253
-
-
Wu, W.1
-
5
-
-
33745255698
-
Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network
-
Chaplot, S., L. M. Patnaik, and N. R. Jagannathan, “Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network,” Biomedical Signal Processing and Control, Vol. 1, No. 1, 86-92, 2006.
-
(2006)
Biomedical Signal Processing and Control
, vol.1
, Issue.1
, pp. 86-92
-
-
Chaplot, S.1
Patnaik, L.M.2
Jagannathan, N.R.3
-
6
-
-
33847043225
-
A Slantlet transform based intelligent system for magnetic resonance brain image classification
-
Maitra, M. and A. Chatterjee, “A Slantlet transform based intelligent system for magnetic resonance brain image classification,” Biomedical Signal Processing and Control, Vol. 1, No. 4, 299-306, Oct. 2006.
-
(2006)
Biomedical Signal Processing and Control
, vol.1
, Issue.4
, pp. 299-306
-
-
Maitra, M.1
Chatterjee, A.2
-
7
-
-
76549108474
-
Hybrid intelligent techniques for MRI brain images classification
-
El-Dahshan, E. S. A., T. Hosny, and A. B. M. Salem, “Hybrid intelligent techniques for MRI brain images classification,” Digital Signal Processing, Vol. 20, No. 2, 433-441, Mar. 2010.
-
(2010)
Digital Signal Processing
, vol.20
, Issue.2
, pp. 433-441
-
-
El-Dahshan, E.1
Hosny, T.2
Salem, A.B.3
-
8
-
-
79958134346
-
Magnetic resonance brain image classification by an improved artificial bee colony algorithm
-
Zhang, Y., L. Wu, and S. Wang, “Magnetic resonance brain image classification by an improved artificial bee colony algorithm,” Progress In Electromagnetics Research, Vol. 116, 65-79, 2011.
-
(2011)
Progress in Electromagnetics Research
, vol.116
, pp. 65-79
-
-
Zhang, Y.1
Wu, L.2
Wang, S.3
-
9
-
-
79953706565
-
A hybrid method for MRI brain image classification
-
Zhang, Y., et al., “A hybrid method for MRI brain image classification,” Expert Systems with Applications, Vol. 38, No. 8, 10049-10053, 2011.
-
(2011)
Expert Systems with Applications
, vol.38
, Issue.8
, pp. 10049-10053
-
-
Zhang, Y.1
-
10
-
-
79960338927
-
Brain tissue classification of MR images using fast fourier transform based expectation-maximization Gaussian mixture model
-
Springer
-
Ramasamy, R. and P. Anandhakumar, “Brain tissue classification of MR images using fast fourier transform based expectation-maximization Gaussian mixture model,” Advances in Computing and Information Technology, 387-398, Springer, 2011.
-
(2011)
Advances in Computing and Information Technology
, pp. 387-398
-
-
Ramasamy, R.1
Anandhakumar, P.2
-
11
-
-
84866525215
-
An MR brain images classifier via principal component analysis and kernel support vector machine
-
Zhang, Y. and L. Wu, “An MR brain images classifier via principal component analysis and kernel support vector machine,” Progress In Electromagnetics Research, Vol. 130, 369-388, 2012.
-
(2012)
Progress in Electromagnetics Research
, vol.130
, pp. 369-388
-
-
Zhang, Y.1
Wu, L.2
-
12
-
-
84884575083
-
Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network
-
Saritha, M., K. P. Joseph, and A. T. Mathew, “Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network,” Pattern Recognition Letters, Vol. 34, No. 16, 2151-2156, Dec. 2013.
-
(2013)
Pattern Recognition Letters
, vol.34
, Issue.16
, pp. 2151-2156
-
-
Saritha, M.1
Joseph, K.P.2
Mathew, A.T.3
-
13
-
-
84929627799
-
Effect of spider-web-plot in MR brain image classification
-
Zhang, Y., et al., “Effect of spider-web-plot in MR brain image classification,” Pattern Recognition Letters, Vol. 62, 14-16, Sep. 1, 2015.
-
(2015)
Pattern Recognition Letters
, vol.62
, pp. 14-16
-
-
Zhang, Y.1
-
14
-
-
84873725415
-
Brain MR image classification using multiscale geometric analysis of ripplet
-
Das, S., M. Chowdhury, and M. K. Kundu, “Brain MR image classification using multiscale geometric analysis of ripplet,” Progress In Electromagnetics Research, Vol. 137, 1-17, 2013.
-
(2013)
Progress in Electromagnetics Research
, vol.137
, pp. 1-17
-
-
Das, S.1
Chowdhury, M.2
Kundu, M.K.3
-
15
-
-
84884870289
-
Robust algorithm for brain magnetic resonance image (MRI) classification based on GARCH variances series
-
Kalbkhani, H., M. G. Shayesteh, and B. Zali-Vargahan, “Robust algorithm for brain magnetic resonance image (MRI) classification based on GARCH variances series,” Biomedical Signal Processing and Control, Vol. 8, No. 6, 909-919, 2013.
-
(2013)
Biomedical Signal Processing and Control
, vol.8
, Issue.6
, pp. 909-919
-
-
Kalbkhani, H.1
Shayesteh, M.G.2
Zali-Vargahan, B.3
-
16
-
-
84893083296
-
Segmentation and classification of brain CT images using combined wavelet statistical texture features
-
Padma, A. and R. Sukanesh, “Segmentation and classification of brain CT images using combined wavelet statistical texture features,” Arabian Journal for Science and Engineering, Vol. 39, No. 2, 767-776, Feb. 2014.
-
(2014)
Arabian Journal for Science and Engineering
, vol.39
, Issue.2
, pp. 767-776
-
-
Padma, A.1
Sukanesh, R.2
-
17
-
-
84899008824
-
Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm
-
El-Dahshan, E. S. A., et al., “Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm,” Expert Systems with Applications, Vol. 41, No. 11, 5526-5545, Sep. 2014.
-
(2014)
Expert Systems with Applications
, vol.41
, Issue.11
, pp. 5526-5545
-
-
El-Dahshan, E.1
-
18
-
-
84930332968
-
Preclinical diagnosis of magnetic resonance (MR) brain images via discrete wavelet packet transform with Tsallis entropy and generalized eigenvalue proximal support vector machine (GEPSVM)
-
Zhang, Y., et al., “Preclinical diagnosis of magnetic resonance (MR) brain images via discrete wavelet packet transform with Tsallis entropy and generalized eigenvalue proximal support vector machine (GEPSVM),” Entropy, Vol. 17, No. 4, 1795-1813, 2015.
-
(2015)
Entropy
, vol.17
, Issue.4
, pp. 1795-1813
-
-
Zhang, Y.1
-
19
-
-
84944456448
-
Detection of pathological brain in MRI scanning based on wavelet-entropy and naive Bayes classifier
-
F. Ortuno and I. Rojas, Eds., Springer International Publishing, Granada, Spain
-
Zhou, X., et al., “Detection of pathological brain in MRI scanning based on wavelet-entropy and naive Bayes classifier,” Bioinformatics and Biomedical Engineering, Vol. 9043, 201-209, F. Ortuno and I. Rojas, Eds., Springer International Publishing, Granada, Spain, 2015.
-
(2015)
Bioinformatics and Biomedical Engineering
, vol.9043
, pp. 201-209
-
-
Zhou, X.1
-
20
-
-
84920501690
-
Combining tissue segmentation and neural network for brain tumor detection
-
Damodharan, S. and D. Raghavan, “Combining tissue segmentation and neural network for brain tumor detection,” International Arab Journal of Information Technology, Vol. 12, No. 1, 42-52, Jan. 2015.
-
(2015)
International Arab Journal of Information Technology
, vol.12
, Issue.1
, pp. 42-52
-
-
Damodharan, S.1
Raghavan, D.2
-
21
-
-
84928688048
-
Automated classification of brain images using wavelet-energy and biogeographybased optimization
-
Yang, G., et al., “Automated classification of brain images using wavelet-energy and biogeographybased optimization,” Multimedia Tools and Applications, 1-17, May 1, 2015.
-
(2015)
Multimedia Tools and Applications, 1-17, May
, pp. 1
-
-
Yang, G.1
-
22
-
-
84937397961
-
Automated classification of brain MR images using wavelet-energy and support vector machines
-
C. Liu, et al. (eds.), Atlantis Press, USA
-
Zhang, G.-S., et al., “Automated classification of brain MR images using wavelet-energy and support vector machines,” Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering, C. Liu, et al. (eds.), 683-686, Atlantis Press, USA, 2015.
-
(2015)
Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
, pp. 683-686
-
-
Zhang, G.-S.1
-
23
-
-
84923171982
-
A simple and intelligent approach for brain MRI classification
-
Nazir, M., F. Wahid, and S. A. Khan, “A simple and intelligent approach for brain MRI classification,” Journal of Intelligent & Fuzzy Systems, Vol. 28, No. 3, 1127-1135, 2015.
-
(2015)
Journal of Intelligent & Fuzzy Systems
, vol.28
, Issue.3
, pp. 1127-1135
-
-
Nazir, M.1
Wahid, F.2
Khan, S.A.3
-
24
-
-
84930681763
-
Detection of subjects and brain regions related to Alzheimers disease using 3D MRI scans based on eigenbrain and machine learning,”
-
Zhang, Y., et al., “Detection of subjects and brain regions related to Alzheimer’s disease using 3D MRI scans based on eigenbrain and machine learning,” Frontiers in Computational Neuroscience, Vol. 66, No. 9, 1-15, 2015.
-
(2015)
Frontiers in Computational Neuroscience
, vol.66
, Issue.9
, pp. 1-15
-
-
Zhang, Y.1
-
25
-
-
84922461060
-
Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor
-
Harikumar, R. and B. V. Kumar, “Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor,” International Journal of Imaging Systems and Technology, Vol. 25, No. 1, 33-40, Mar. 2015.
-
(2015)
International Journal of Imaging Systems and Technology
, vol.25
, Issue.1
, pp. 33-40
-
-
Harikumar, R.1
Kumar, B.V.2
-
26
-
-
84929610466
-
Feed-forward neural network optimized by hybridization of PSO and ABC for abnormal brain detection
-
Wang, S., et al., “Feed-forward neural network optimized by hybridization of PSO and ABC for abnormal brain detection,” International Journal of Imaging Systems and Technology, Vol. 25, No. 2, 153-164, 2015.
-
(2015)
International Journal of Imaging Systems and Technology
, vol.25
, Issue.2
, pp. 153-164
-
-
Wang, S.1
-
27
-
-
84931263154
-
Detection of Alzheimers disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC,”
-
Zhang, Y., et al., “Detection of Alzheimer’s disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC,” Biomedical Signal Processing and Control, Vol. 21, 58-73, Aug. 2015.
-
(2015)
Biomedical Signal Processing and Control
, vol.21
, pp. 58-73
-
-
Zhang, Y.1
-
28
-
-
60249085301
-
Application of adaptive neuro-fuzzy inference system for vigilance level estimation by using wavelet-entropy feature extraction
-
Yildiz, A., et al., “Application of adaptive neuro-fuzzy inference system for vigilance level estimation by using wavelet-entropy feature extraction,” Expert Systems with Applications, Vol. 36, No. 4, 7390-7399, May 2009.
-
(2009)
Expert Systems with Applications
, vol.36
, Issue.4
, pp. 7390-7399
-
-
Yildiz, A.1
-
29
-
-
49549089775
-
Weights optimization of neural network via improved BCO approach
-
Zhang, Y.-D. and L. Wu, “Weights optimization of neural network via improved BCO approach,” Progress In Electromagnetics Research, Vol. 83, 185-198, 2008.
-
(2008)
Progress in Electromagnetics Research
, vol.83
, pp. 185-198
-
-
Zhang, Y.-D.1
Wu, L.2
-
30
-
-
84924598881
-
A novel demodulation system based on continuous wavelet transform
-
Fang, L., L. Wu, and Y. Zhang, “A novel demodulation system based on continuous wavelet transform,” Mathematical Problems in Engineering, Vol. 2015, 9, 2015.
-
(2015)
Mathematical Problems in Engineering
, vol.2015
, pp. 9
-
-
Fang, L.1
Wu, L.2
Zhang, Y.3
-
31
-
-
84924086238
-
Wavelet kernel entropy component analysis with application to industrial process monitoring
-
Yang, Y. H., et al., “Wavelet kernel entropy component analysis with application to industrial process monitoring,” Neurocomputing, Vol. 147, 395-402, Jan. 2015.
-
(2015)
Neurocomputing
, vol.147
, pp. 395-402
-
-
Yang, Y.H.1
-
32
-
-
84921675256
-
A survey on detection of brain tumor from MRI brain images
-
Aswathy, S. U., G. G. Deva Dhas, and S. S. Kumar, “A survey on detection of brain tumor from MRI brain images,” 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 871-877, 2014.
-
(2014)
2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT)
, pp. 871-877
-
-
Aswathy, S.U.1
Deva Dhas, G.G.2
Kumar, S.S.3
-
33
-
-
84904625723
-
Improved radio frequency identification indoor localization method via radial basis function neural network
-
Guo, D., et al., “Improved radio frequency identification indoor localization method via radial basis function neural network,” Mathematical Problems in Engineering, 2014.
-
(2014)
Mathematical Problems in Engineering
-
-
Guo, D.1
-
34
-
-
84893829347
-
An incremental learning preprocessor for feed-forward neural network
-
Fuangkhon, P., “An incremental learning preprocessor for feed-forward neural network,” Artificial Intelligence Review, Vol. 41, No. 2, 183-210, Feb. 2014.
-
(2014)
Artificial Intelligence Review
, vol.41
, Issue.2
, pp. 183-210
-
-
Fuangkhon, P.1
-
35
-
-
83955165320
-
Artificial neural network model for prediction of cold spot temperature in retort sterilization of starch-based foods
-
Llave, Y. A., T. Hagiwara, and T. Sakiyama, “Artificial neural network model for prediction of cold spot temperature in retort sterilization of starch-based foods,” Journal of Food Engineering, Vol. 109, No. 3, 553-560, 2012.
-
(2012)
Journal of Food Engineering
, vol.109
, Issue.3
, pp. 553-560
-
-
Llave, Y.A.1
Hagiwara, T.2
Sakiyama, T.3
-
36
-
-
59849122121
-
Applications of information theory, genetic algorithms, and neural models to predict oil flow
-
Ludwig, Jr, O., et al., “Applications of information theory, genetic algorithms, and neural models to predict oil flow,” Communications in Nonlinear Science and Numerical Simulation, Vol. 14, No. 7, 2870-2885, 2009.
-
(2009)
Communications in Nonlinear Science and Numerical Simulation
, vol.14
, Issue.7
, pp. 2870-2885
-
-
Ludwig, O.1
-
37
-
-
84919787953
-
Prediction of the binary density of the ionic liquids plus water using backpropagated feed forward artificial neural network
-
Shojaee, S. A., et al., “Prediction of the binary density of the ionic liquids plus water using backpropagated feed forward artificial neural network,” Chemical Industry & Chemical Engineering Quarterly, Vol. 20, No. 3, 325-338, Jul.-Sep. 2014.
-
(2014)
Chemical Industry & Chemical Engineering Quarterly
, vol.20
, Issue.3
, pp. 325-338
-
-
Shojaee, S.A.1
-
38
-
-
84904467844
-
Impact of learning rate and momentum factor in the performance of back-propagation neural network to identify internal dynamics of chaotic motion
-
Karmakar, S., G. Shrivastava, and M. K. Kowar, “Impact of learning rate and momentum factor in the performance of back-propagation neural network to identify internal dynamics of chaotic motion,” Kuwait Journal of Science, Vol. 41, No. 2, 151-174, May 2014.
-
(2014)
Kuwait Journal of Science
, vol.41
, Issue.2
, pp. 151-174
-
-
Karmakar, S.1
Shrivastava, G.2
Kowar, M.K.3
-
39
-
-
84907546172
-
Modeling slump of ready mix concrete using genetic algorithms assisted training of artificial neural networks
-
Chandwani, V., V. Agrawal, and R. Nagar, “Modeling slump of ready mix concrete using genetic algorithms assisted training of artificial neural networks,” Expert Systems with Applications, Vol. 42, No. 2, 885-893, Feb. 2015.
-
(2015)
Expert Systems with Applications
, vol.42
, Issue.2
, pp. 885-893
-
-
Chandwani, V.1
Agrawal, V.2
Nagar, R.3
-
40
-
-
84903280064
-
Integration of artificial neural network and simulated annealing algorithm to optimize deep drawing process
-
Manoochehri, M. and F. Kolahan, “Integration of artificial neural network and simulated annealing algorithm to optimize deep drawing process,” International Journal of Advanced Manufacturing Technology, Vol. 73, Nos. 14, 241-249, Jul. 2014.
-
(2014)
International Journal of Advanced Manufacturing Technology
, vol.73
, Issue.14
, pp. 241-249
-
-
Manoochehri, M.1
Kolahan, F.2
-
41
-
-
84920252463
-
An efficient model based on artificial bee colony optimization algorithm with neural networks for electric load forecasting
-
Awan, S. M., et al., “An efficient model based on artificial bee colony optimization algorithm with neural networks for electric load forecasting,” Neural Computing & Applications, Vol. 25, Nos. 7-8, 1967-1978, Dec. 2014.
-
(2014)
Neural Computing & Applications
, vol.25
, Issue.7-8
, pp. 1967-1978
-
-
Awan, S.M.1
-
42
-
-
57249115093
-
Biogeography-based optimization
-
Simon, D., “Biogeography-based optimization,” IEEE Transactions on Evolutionary Computation, Vol. 12, No. 6, 702-713, Dec. 2008.
-
(2008)
IEEE Transactions on Evolutionary Computation
, vol.12
, Issue.6
, pp. 702-713
-
-
Simon, D.1
-
43
-
-
84908308703
-
Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks
-
Momeni, E., et al., “Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks,” Measurement, Vol. 60, 50-63, Jan. 2015.
-
(2015)
Measurement
, vol.60
, pp. 50-63
-
-
Momeni, E.1
-
44
-
-
84901653528
-
Adaptive biogeography based predator-prey optimization technique for optimal power flow
-
Christy, A. A. and P. Raj, “Adaptive biogeography based predator-prey optimization technique for optimal power flow,” International Journal of Electrical Power & Energy Systems, Vol. 62, 344-352, Nov. 2014.
-
(2014)
International Journal of Electrical Power & Energy Systems
, vol.62
, pp. 344-352
-
-
Christy, A.A.1
Raj, P.2
-
45
-
-
84905364371
-
Biogeography-based particle swarm optimization with fuzzy elitism and its applications to constrained engineering problems
-
Guo, W. A., et al., “Biogeography-based particle swarm optimization with fuzzy elitism and its applications to constrained engineering problems,” Engineering Optimization, Vol. 46, No. 11, 1465-1484, Nov. 2014.
-
(2014)
Engineering Optimization
, vol.46
, Issue.11
, pp. 1465-1484
-
-
Guo, W.A.1
-
46
-
-
79957441310
-
A probabilistic analysis of a simplified biogeography-based optimization algorithm
-
Simon, D., “A probabilistic analysis of a simplified biogeography-based optimization algorithm,” Evolutionary Computation, Vol. 19, No. 2, 167-188, Summer 2011.
-
(2011)
Evolutionary Computation
, vol.19
, Issue.2
, pp. 167-188
-
-
Simon, D.1
-
47
-
-
84892614873
-
“Classification of Alzheimer disease based on structural magnetic resonance imaging by kernel support vector machine decision tree
-
Zhang, Y., S. Wang, and Z. Dong, “Classification of Alzheimer disease based on structural magnetic resonance imaging by kernel support vector machine decision tree,” Progress In Electromagnetics Research, Vol. 144, 171-184, 2014.
-
(2014)
Progress in Electromagnetics Research
, vol.144
, pp. 171-184
-
-
Zhang, Y.1
Wang, S.2
Dong, Z.3
-
48
-
-
84900480300
-
Probabilistic opposition-based particle swarm optimization with velocity clamping
-
Shahzad, F., S. Masood, and N. K. Khan, “Probabilistic opposition-based particle swarm optimization with velocity clamping,” Knowledge and Information Systems, Vol. 39, No. 3, 703-737, Jun. 2014.
-
(2014)
Knowledge and Information Systems
, vol.39
, Issue.3
, pp. 703-737
-
-
Shahzad, F.1
Masood, S.2
Khan, N.K.3
-
49
-
-
0036464756
-
The particle swarm — Explosion, stability, and convergence in a multidimensional complex space
-
Clerc, M. and J. Kennedy, “The particle swarm — Explosion, stability, and convergence in a multidimensional complex space,” IEEE Transactions on Evolutionary Computation, Vol. 6, No. 1, 58-73, Feb. 2002.
-
(2002)
IEEE Transactions on Evolutionary Computation
, vol.6
, Issue.1
, pp. 58-73
-
-
Clerc, M.1
Kennedy, J.2
-
50
-
-
85027936669
-
Research of biogeography particle swarm optimization for robot path planning
-
Mo, H. W. and L. F. Xu, “Research of biogeography particle swarm optimization for robot path planning,” Neurocomputing, Vol. 148, 91-99, Jan. 2015.
-
(2015)
Neurocomputing
, vol.148
, pp. 91-99
-
-
Mo, H.W.1
Xu, L.F.2
-
51
-
-
84907549296
-
Biogeography-based optimization for optimal job scheduling in cloud computing
-
Kim, S. S., et al., “Biogeography-based optimization for optimal job scheduling in cloud computing,” Applied Mathematics and Computation, Vol. 247, 266-280, Nov. 2014.
-
(2014)
Applied Mathematics and Computation
, vol.247
, pp. 266-280
-
-
Kim, S.S.1
-
52
-
-
84886726325
-
A recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problems
-
Kiran, M. S. and M. Gunduz, “A recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problems,” Applied Soft Computing, Vol. 13, No. 4, 2188-2203, Apr. 2013.
-
(2013)
Applied Soft Computing
, vol.13
, Issue.4
, pp. 2188-2203
-
-
Kiran, M.S.1
Gunduz, M.2
-
53
-
-
84901367057
-
Cell assignment in hybrid CMOS/nanodevices architecture using a PSO/SA hybrid algorithm
-
Sait, S. M., A. T. Sheikh, and A. H. El-Maleh, “Cell assignment in hybrid CMOS/nanodevices architecture using a PSO/SA hybrid algorithm,” Journal of Applied Research and Technology, Vol. 11, 653-664, Oct. 2013.
-
(2013)
Journal of Applied Research and Technology
, vol.11
, pp. 653-664
-
-
Sait, S.M.1
Sheikh, A.T.2
El-Maleh, A.H.3
-
54
-
-
70350022524
-
Remote-sensing image classification based on an improved probabilistic neural network
-
Zhang, Y., et al., “Remote-sensing image classification based on an improved probabilistic neural network,” Sensors, Vol. 9, No. 9, 7516-7539, 2009.
-
(2009)
Sensors
, vol.9
, Issue.9
, pp. 7516-7539
-
-
Zhang, Y.1
-
55
-
-
84904977190
-
Fruit classification using computer vision and feedforward neural-network
-
Zhang, Y., et al., “Fruit classification using computer vision and feedforward neural-network,” Journal of Food Engineering, Vol. 143, No. 0, 167-177, 2014.
-
(2014)
Journal of Food Engineering
, vol.143
, pp. 167-177
-
-
Zhang, Y.1
-
56
-
-
84911441675
-
Improving the spectral resolution and spectral fitting of 1H MRSI data from human calf muscle by the SPREAD technique
-
Dong, Z., et al., “Improving the spectral resolution and spectral fitting of 1H MRSI data from human calf muscle by the SPREAD technique,” NMR in Biomedicine, Vol. 27, No. 11, 1325-1332, 2014.
-
(2014)
NMR in Biomedicine
, vol.27
, Issue.11
, pp. 1325-1332
-
-
Dong, Z.1
-
57
-
-
84901000436
-
Diagnosis of the wear of gears in the gearbox using the wavelet packet transform
-
Figlus, T. and M. Stanczyk, “Diagnosis of the wear of gears in the gearbox using the wavelet packet transform,” Metalurgija, Vol. 53, No. 4, 673-676, Oct.-Dec. 2014.
-
(2014)
Metalurgija
, vol.53
, Issue.4
, pp. 673-676
-
-
Figlus, T.1
Stanczyk, M.2
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