메뉴 건너뛰기




Volumn 77, Issue 17, 2018, Pages 21825-21845

Voxelwise detection of cerebral microbleed in CADASIL patients by leaky rectified linear unit and early stopping

Author keywords

CADASIL; Cerebral microbleed; Class imbalanced problem; Leaky rectified linear unit; Logistic sigmoid; Magnetic resonance imaging; Susceptibility weighted imaging

Indexed keywords

BRAIN MAPPING; CHEMICAL ACTIVATION; FEEDFORWARD NEURAL NETWORKS; MAGNETIC RESONANCE IMAGING; NETWORK LAYERS;

EID: 85009726009     PISSN: 13807501     EISSN: 15737721     Source Type: Journal    
DOI: 10.1007/s11042-017-4383-9     Document Type: Article
Times cited : (53)

References (67)
  • 1
    • 84965100085 scopus 로고    scopus 로고
    • Artificial intelligence and its applications 2014
    • Agarwal P (2016) Artificial intelligence and its applications 2014. Math Probl Eng. doi:10.1155/2016/3871575
    • (2016) Math Probl Eng
    • Agarwal, P.1
  • 2
    • 85051146622 scopus 로고    scopus 로고
    • Toward an optimal convolutional neural network for traffic sign recognition
    • Barcelona: Spie-Int Soc Optical Engineering
    • Aghdam HH et al (2015)Toward an optimal convolutional neural network for traffic sign recognition. In 8th International Conference on Machine Vision. Barcelona: Spie-Int Soc Optical Engineering. p. 98750K
    • (2015) 8Th International Conference on Machine Vision , pp. 98750K
    • Aghdam, H.H.1
  • 3
    • 84951769079 scopus 로고    scopus 로고
    • Recognizing traffic signs using a practical deep neural network
    • Lisbon, PORTUGAL, Springer-Verlag Berlin
    • Aghdam HH et al (2016) Recognizing traffic signs using a practical deep neural network. In 2nd Iberian Robotics Conference (ROBOT). Lisbon, PORTUGAL: Springer-Verlag Berlin pp 399-410
    • (2016) 2Nd Iberian Robotics Conference (ROBOT) , pp. 399-410
    • Aghdam, H.H.1
  • 4
    • 84962349341 scopus 로고    scopus 로고
    • Can-CSC-GBE: developing cost-sensitive classifier with Gentleboost ensemble for breast cancer classification using protein amino acids and imbalanced data
    • Ali S et al (2016) Can-CSC-GBE: developing cost-sensitive classifier with Gentleboost ensemble for breast cancer classification using protein amino acids and imbalanced data. Comput Biol Med 73:38–46
    • (2016) Comput Biol Med , vol.73 , pp. 38-46
    • Ali, S.1
  • 5
    • 84958104787 scopus 로고    scopus 로고
    • Classifying imbalanced data in distance-based feature space
    • Ando S (2016) Classifying imbalanced data in distance-based feature space. Knowl Inf Syst 46(3):707–730
    • (2016) Knowl Inf Syst , vol.46 , Issue.3 , pp. 707-730
    • Ando, S.1
  • 6
  • 7
    • 84899964299 scopus 로고    scopus 로고
    • Artificial intelligence and its applications
    • Balochian S (2014) Artificial intelligence and its applications. Math Probl Eng. doi:10.1155/2014/840491
    • (2014) Math Probl Eng
    • Balochian, S.1
  • 8
    • 79959235240 scopus 로고    scopus 로고
    • Semiautomated detection of cerebral microbleeds in magnetic resonance images
    • Barnes SRS et al (2011) Semiautomated detection of cerebral microbleeds in magnetic resonance images. Magn Reson Imaging 29(6):844–852
    • (2011) Magn Reson Imaging , vol.29 , Issue.6 , pp. 844-852
    • Barnes, S.R.S.1
  • 9
    • 84951872496 scopus 로고    scopus 로고
    • Deep dropout artificial neural networks for recognising digits and characters in natural images
    • Istanbul, Springer Int Publishing Ag
    • Barrow E et al (2015) Deep dropout artificial neural networks for recognising digits and characters in natural images. In 22nd International Conference on Neural Information Processing (ICONIP). Istanbul: Springer Int Publishing Ag. pp. 29–37
    • (2015) 22Nd International Conference on Neural Information Processing (ICONIP) , pp. 29-37
    • Barrow, E.1
  • 10
    • 84874834481 scopus 로고    scopus 로고
    • Computer-aided detection of radiation-induced cerebral microbleeds on susceptibility-weighted MR images
    • Bian W et al (2013) Computer-aided detection of radiation-induced cerebral microbleeds on susceptibility-weighted MR images. Neuroimage-Clinical 2:282–290
    • (2013) Neuroimage-Clinical , vol.2 , pp. 282-290
    • Bian, W.1
  • 11
    • 84988660816 scopus 로고    scopus 로고
    • Employing speeded scaled conjugate gradient algorithm for multiple contiguous feature vector frames: An approach for traffic density state estimation
    • Nagpur: Elsevier Science Bv
    • Borkar P et al (2016) Employing speeded scaled conjugate gradient algorithm for multiple contiguous feature vector frames: an approach for traffic density state estimation. In 1st International conference on information security & privacy. Nagpur: Elsevier Science Bv. pp. 740–747
    • (2016) 1St International Conference on Information Security & Privacy , pp. 740-747
    • Borkar, P.1
  • 12
    • 84992744390 scopus 로고    scopus 로고
    • Sensorineural hearing loss detection via discrete wavelet transform and principal component analysis combined with generalized eigenvalue proximal support vector machine and Tikhonov regularization
    • Online
    • Chen Y, Chen X-Q (2016) Sensorineural hearing loss detection via discrete wavelet transform and principal component analysis combined with generalized eigenvalue proximal support vector machine and Tikhonov regularization. Multimedia Tools and Applications, doi:10.1007/s11042-016-4087-6 (Online)
    • (2016) Multimedia Tools and Applications
    • Chen, Y.1    Chen, X.-Q.2
  • 13
    • 84949292725 scopus 로고    scopus 로고
    • Detection of dendritic spines using wavelet-based conditional symmetric analysis and regularized morphological shared-weight neural networks
    • Chen M et al (2015a) Detection of dendritic spines using wavelet-based conditional symmetric analysis and regularized morphological shared-weight neural networks. Comput Math Methods Med. doi:10.1155/2015/454076
    • (2015) Comput Math Methods Med
    • Chen, M.1
  • 14
    • 84924862864 scopus 로고    scopus 로고
    • AIWAC: affective interaction through wearable computing and cloud technology
    • Chen M et al (2015b) AIWAC: affective interaction through wearable computing and cloud technology. IEEE Wirel Commun 22(1):20–27
    • (2015) IEEE Wirel Commun , vol.22 , Issue.1 , pp. 20-27
    • Chen, M.1
  • 15
    • 84890527827 scopus 로고    scopus 로고
    • Improving deep neural networks for lvcsr using rectified linear units and dropout
    • Vancouver: IEEE
    • Dahl GE et al (2013) Improving deep neural networks for lvcsr using rectified linear units and dropout. In International Conference on Acoustics, Speech And Signal Processing. Vancouver: IEEE. pp. 8609–8613
    • (2013) International Conference on Acoustics, Speech and Signal Processing , pp. 8609-8613
    • Dahl, G.E.1
  • 16
    • 84946487721 scopus 로고    scopus 로고
    • Long-term streamflow forecasts by adaptive neuro-fuzzy inference system using satellite images and K-fold cross-validation (case study: Dez, Iran)
    • Esmaeelzadeh SR et al (2015) Long-term streamflow forecasts by adaptive neuro-fuzzy inference system using satellite images and K-fold cross-validation (case study: Dez, Iran). KSCE J Civ Eng 19(7):2298–2306
    • (2015) KSCE J Civ Eng , vol.19 , Issue.7 , pp. 2298-2306
    • Esmaeelzadeh, S.R.1
  • 18
    • 84955259585 scopus 로고    scopus 로고
    • Computer-aided detection of cerebral microbleeds in susceptibility-weighted imaging
    • Fazlollahi A et al (2015) Computer-aided detection of cerebral microbleeds in susceptibility-weighted imaging. Comput Med Imaging Graph 46:269–276
    • (2015) Comput Med Imaging Graph , vol.46 , pp. 269-276
    • Fazlollahi, A.1
  • 19
    • 84929610466 scopus 로고    scopus 로고
    • Feed-forward neural network optimized by hybridization of PSO and ABC for abnormal brain detection
    • Feng C (2015) Feed-forward neural network optimized by hybridization of PSO and ABC for abnormal brain detection. Int J Imaging Syst Technol 25(2):153–164
    • (2015) Int J Imaging Syst Technol , vol.25 , Issue.2 , pp. 153-164
    • Feng, C.1
  • 20
    • 84918594213 scopus 로고    scopus 로고
    • Double circuit EHV transmission lines fault location with RBF based support vector machine and reconstructed input scaled conjugate gradient based neural network
    • Gayathri K, Kumarappan N (2015) Double circuit EHV transmission lines fault location with RBF based support vector machine and reconstructed input scaled conjugate gradient based neural network. International Journal Of Computational Intelligence Systems 8(1):95–105
    • (2015) International Journal Of Computational Intelligence Systems , vol.8 , Issue.1 , pp. 95-105
    • Gayathri, K.1    Kumarappan, N.2
  • 21
    • 84937036320 scopus 로고    scopus 로고
    • Susceptibility-weighted phase imaging and oxygen extraction fraction measurement during sedation and sedation recovery using 7 T MRI
    • Goodwin JA et al (2015) Susceptibility-weighted phase imaging and oxygen extraction fraction measurement during sedation and sedation recovery using 7 T MRI. J Neuroimaging 25(4):575–581
    • (2015) J Neuroimaging , vol.25 , Issue.4 , pp. 575-581
    • Goodwin, J.A.1
  • 22
    • 58649115794 scopus 로고    scopus 로고
    • Cerebral microbleeds: a guide to detection and interpretation
    • Greenberg SM et al (2009) Cerebral microbleeds: a guide to detection and interpretation. Lancet Neurol 8(2):165–174
    • (2009) Lancet Neurol , vol.8 , Issue.2 , pp. 165-174
    • Greenberg, S.M.1
  • 23
    • 73349095046 scopus 로고    scopus 로고
    • The microbleed anatomical rating scale (MARS) reliability of a tool to map brain microbleeds
    • Gregoire SM et al (2009) The microbleed anatomical rating scale (MARS) reliability of a tool to map brain microbleeds. Neurology 73(21):1759–1766
    • (2009) Neurology , vol.73 , Issue.21 , pp. 1759-1766
    • Gregoire, S.M.1
  • 25
    • 34347379379 scopus 로고    scopus 로고
    • Dynamics of dot-like hemosiderin spots on T2*-weighted MRIs associated with stroke recurrence
    • Imaizumi T et al (2007) Dynamics of dot-like hemosiderin spots on T2*-weighted MRIs associated with stroke recurrence. J Neuroimaging 17(3):204–210
    • (2007) J Neuroimaging , vol.17 , Issue.3 , pp. 204-210
    • Imaizumi, T.1
  • 26
    • 84904977190 scopus 로고    scopus 로고
    • Fruit classification using computer vision and feedforward neural network
    • Ji G (2014) Fruit classification using computer vision and feedforward neural network. J Food Eng 143:167–177
    • (2014) J Food Eng , vol.143 , pp. 167-177
    • Ji, G.1
  • 27
    • 84963772287 scopus 로고    scopus 로고
    • A bayesian modelling approach with balancing informative prior for analysing imbalanced data
    • Klein K et al (2016) A bayesian modelling approach with balancing informative prior for analysing imbalanced data. Plos One 11(4):e0152700
    • (2016) Plos One , vol.11 , Issue.4
    • Klein, K.1
  • 28
    • 40149100659 scopus 로고    scopus 로고
    • A sigmoid function is the best fit for the ascending limb of the Hoffmann reflex recruitment curve
    • Klimstra M, Zehr EP (2008) A sigmoid function is the best fit for the ascending limb of the Hoffmann reflex recruitment curve. Exp Brain Res 186(1):93–105
    • (2008) Exp Brain Res , vol.186 , Issue.1 , pp. 93-105
    • Klimstra, M.1    Zehr, E.P.2
  • 29
    • 84928914464 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy inference systems with k-fold cross-validation for energy expenditure predictions based on heart rate
    • Kolus A et al (2015) Adaptive neuro-fuzzy inference systems with k-fold cross-validation for energy expenditure predictions based on heart rate. Appl Ergon 50:68–78
    • (2015) Appl Ergon , vol.50 , pp. 68-78
    • Kolus, A.1
  • 30
    • 84855443719 scopus 로고    scopus 로고
    • Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform
    • Kuijf HJ et al (2012) Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform. NeuroImage 59(3):2266–2273
    • (2012) NeuroImage , vol.59 , Issue.3 , pp. 2266-2273
    • Kuijf, H.J.1
  • 31
    • 84924388345 scopus 로고    scopus 로고
    • An iterative undersampling of extremely imbalanced data using csvm
    • Milan, ITALY: Spie-Int Soc Optical Engineering
    • Lee JB Lee JH (2015) An iterative undersampling of extremely imbalanced data using csvm. in 7th international conference on machine vision. Milan, ITALY: Spie-Int Soc Optical Engineering. pp. 3460–3471
    • (2015) 7Th International Conference on Machine Vision , pp. 3460-3471
    • Lee Jb Lee, J.H.1
  • 32
    • 84894431937 scopus 로고    scopus 로고
    • A new susceptibility-weighted image reconstruction method for the reduction of background phase artifacts
    • Lee Y et al (2014) A new susceptibility-weighted image reconstruction method for the reduction of background phase artifacts. Magn Reson Med 71(3):1324–1335
    • (2014) Magn Reson Med , vol.71 , Issue.3 , pp. 1324-1335
    • Lee, Y.1
  • 33
    • 84982166974 scopus 로고    scopus 로고
    • Moonlighting transcriptional activation function of a fungal sulfur metabolism enzyme
    • Levati E et al (2016) Moonlighting transcriptional activation function of a fungal sulfur metabolism enzyme. Sci Report 6:25165
    • (2016) Sci Report , vol.6 , pp. 25165
    • Levati, E.1
  • 34
    • 84882777522 scopus 로고    scopus 로고
    • Review and performance analysis of single hidden layer sequential learning algorithms of feed-forward neural networks
    • Li B, Rong XW (2013) Review and performance analysis of single hidden layer sequential learning algorithms of feed-forward neural networks. In 25th chinese control and decision conference. Guiyang, Peoples R China: IEEE. pp. 2170–2175
    • (2013) In 25Th Chinese Control and Decision Conference. Guiyang, Peoples R China: IEEE , pp. 2170-2175
    • Li, B.1    Rong, X.W.2
  • 35
    • 84983111549 scopus 로고    scopus 로고
    • An image retrieval method for binary images based on DBN and softmax classifier
    • Liao B et al (2015) An image retrieval method for binary images based on DBN and softmax classifier. IETE Tech Rev 32(4):294–303
    • (2015) IETE Tech Rev , vol.32 , Issue.4 , pp. 294-303
    • Liao, B.1
  • 36
    • 85000692374 scopus 로고    scopus 로고
    • Magnetic resonance brain image classification via stationary wavelet transform and generalized eigenvalue proximal support vector machine
    • Liu A (2015) Magnetic resonance brain image classification via stationary wavelet transform and generalized eigenvalue proximal support vector machine. Journal of Medical Imaging and Health Informatics 5(7):1395–1403
    • (2015) Journal of Medical Imaging and Health Informatics , vol.5 , Issue.7 , pp. 1395-1403
    • Liu, A.1
  • 37
    • 85012969638 scopus 로고    scopus 로고
    • Facial emotion recognition based on biorthogonal wavelet entropy, fuzzy support vector machine, and stratified cross validation
    • Lu HM (2016) Facial emotion recognition based on biorthogonal wavelet entropy, fuzzy support vector machine, and stratified cross validation. IEEE Access 4:8375–8385
    • (2016) IEEE Access , vol.4 , pp. 8375-8385
    • Lu, H.M.1
  • 38
    • 77951279265 scopus 로고    scopus 로고
    • Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy
    • Murray V et al (2010) Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy. IEEE Trans Image Process 19(5):1138–1152
    • (2010) IEEE Trans Image Process , vol.19 , Issue.5 , pp. 1138-1152
    • Murray, V.1
  • 39
    • 84955267982 scopus 로고    scopus 로고
    • A novel activation function for multilayer feed-forward neural networks
    • Njikam ANS, Zhao H (2016) A novel activation function for multilayer feed-forward neural networks. Appl Intell 45(1):75–82
    • (2016) Appl Intell , vol.45 , Issue.1 , pp. 75-82
    • Njikam, A.N.S.1    Zhao, H.2
  • 40
    • 84961390107 scopus 로고    scopus 로고
    • The noisy expectation-maximization algorithm for multiplicative noise injection
    • Article ID: 1650007
    • Osoba O, Kosko B (2016) The noisy expectation-maximization algorithm for multiplicative noise injection. Fluctuation And Noise Letters 15(1):23 Article ID: 1650007
    • (2016) Fluctuation And Noise Letters , vol.15 , Issue.1 , pp. 23
    • Osoba, O.1    Kosko, B.2
  • 41
    • 84959018146 scopus 로고    scopus 로고
    • Image processing methods to elucidate spatial characteristics of retinal microglia after optic nerve transection
    • Peng B et al (2016) Image processing methods to elucidate spatial characteristics of retinal microglia after optic nerve transection. Scientific Reports 6:21816
    • (2016) Scientific Reports , vol.6 , pp. 21816
    • Peng, B.1
  • 42
    • 84943395798 scopus 로고    scopus 로고
    • Cerebral microbleed segmentation from susceptibility weighted images
    • Roy S et al (2015) Cerebral microbleed segmentation from susceptibility weighted images. Proc SPIE 9413. doi:10.1117/12.2082237
    • (2015) Proc SPIE , vol.9413
    • Roy, S.1
  • 43
    • 84969171492 scopus 로고    scopus 로고
    • The NOTCH3 score: a pre-clinical CADASIL biomarker in a novel human genomic NOTCH3 transgenic mouse model with early progressive vascular NOTCH3 accumulation
    • Rutten JW et al (2015) The NOTCH3 score: a pre-clinical CADASIL biomarker in a novel human genomic NOTCH3 transgenic mouse model with early progressive vascular NOTCH3 accumulation. Acta Neuropathol Commun 3:89
    • (2015) Acta Neuropathol Commun , vol.3 , pp. 89
    • Rutten, J.W.1
  • 44
    • 79952972941 scopus 로고    scopus 로고
    • Microbleed detection using automated segmentation (midas): a new method applicable to standard clinical mr images
    • Seghier ML et al (2011) Microbleed detection using automated segmentation (midas): a new method applicable to standard clinical mr images. Plos One 6(3):e17547
    • (2011) Plos One , vol.6 , Issue.3
    • Seghier, M.L.1
  • 45
    • 79953900986 scopus 로고    scopus 로고
    • Image enhancement for fingerprint minutiae-based algorithms using clahe, standard deviation analysis and sliding neighborhood
    • San Francisco, Int Assoc Engineers-IAENG
    • Sepasian M et al. (2008) Image enhancement for fingerprint minutiae-based algorithms using clahe, standard deviation analysis and sliding neighborhood. In world congress on engineering and computer science. San Francisco: Int Assoc Engineers-IAENG. pp. 1199–1203
    • (2008) In World Congress on Engineering and Computer Science , pp. 1199-1203
  • 46
    • 84963954567 scopus 로고    scopus 로고
    • Inverse scattering using a joint L1-L2 norm-based regularization
    • Shah P et al (2016) Inverse scattering using a joint L1-L2 norm-based regularization. IEEE Trans Antennas Propag 64(4):1373–1384
    • (2016) IEEE Trans Antennas Propag , vol.64 , Issue.4 , pp. 1373-1384
    • Shah, P.1
  • 47
    • 78650950371 scopus 로고    scopus 로고
    • Comparison of early stopping criteria for neural-network-based subpixel classification
    • Shao Y et al (2011) Comparison of early stopping criteria for neural-network-based subpixel classification. IEEE Geosci Remote Sens Lett 8(1):113–117
    • (2011) IEEE Geosci Remote Sens Lett , vol.8 , Issue.1 , pp. 113-117
    • Shao, Y.1
  • 48
    • 84976389312 scopus 로고    scopus 로고
    • CADASIL: migraine, encephalopathy, stroke and their inter-relationships
    • Tan RYY, Markus HS (2016) CADASIL: migraine, encephalopathy, stroke and their inter-relationships. Plos One 11(6):e0157613
    • (2016) Plos One , vol.11 , Issue.6
    • Tan, R.Y.Y.1    Markus, H.S.2
  • 49
    • 84974625093 scopus 로고    scopus 로고
    • Risk of symptomatic intracerebral hemorrhage after intravenous thrombolysis in patients with acute ischemic stroke and high cerebral microbleed burden a meta-analysis
    • Tsivgoulis G et al (2016) Risk of symptomatic intracerebral hemorrhage after intravenous thrombolysis in patients with acute ischemic stroke and high cerebral microbleed burden a meta-analysis. JAMA Neurology 73(6):675–683
    • (2016) JAMA Neurology , vol.73 , Issue.6 , pp. 675-683
    • Tsivgoulis, G.1
  • 50
    • 85051667646 scopus 로고    scopus 로고
    • Clopedogril loading in acute ischemic stroke patients with cerebral microbleed does not increase the risk of hemorrhage
    • Valmoria MS et al (2014) Clopedogril loading in acute ischemic stroke patients with cerebral microbleed does not increase the risk of hemorrhage. Ann Neurol 76:S88–S89
    • (2014) Ann Neurol , vol.76 , pp. S88-S89
    • Valmoria, M.S.1
  • 51
    • 84928233256 scopus 로고    scopus 로고
    • Cerebral microbleed causing an acute stroke-like episode in a CADASIL patient
    • Vitali P et al (2014) Cerebral microbleed causing an acute stroke-like episode in a CADASIL patient. Can J Neurol Sci 41(5):661–663
    • (2014) Can J Neurol Sci , vol.41 , Issue.5 , pp. 661-663
    • Vitali, P.1
  • 52
    • 84940487338 scopus 로고    scopus 로고
    • Fruit classification by wavelet-entropy and feedforward neural network trained by fitness-scaled chaotic ABC and biogeography-based optimization
    • Wei L (2015) Fruit classification by wavelet-entropy and feedforward neural network trained by fitness-scaled chaotic ABC and biogeography-based optimization. Entropy 17(8):5711–5728
    • (2015) Entropy , vol.17 , Issue.8 , pp. 5711-5728
    • Wei, L.1
  • 53
    • 84944884784 scopus 로고    scopus 로고
    • Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) - literature review apropos an autopsy case
    • Wesolowski W et al (2015) Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) - literature review apropos an autopsy case. Pol J Pathol 66(3):323–329
    • (2015) Pol J Pathol , vol.66 , Issue.3 , pp. 323-329
    • Wesolowski, W.1
  • 54
    • 79953706565 scopus 로고    scopus 로고
    • A hybrid method for MRI brain image classification
    • Wu L (2011) A hybrid method for MRI brain image classification. Expert Syst Appl 38(8):10049–10053
    • (2011) Expert Syst Appl , vol.38 , Issue.8 , pp. 10049-10053
    • Wu, L.1
  • 55
    • 84976232120 scopus 로고    scopus 로고
    • Fruit classification by biogeography-based optimization and feedforward neural network
    • Wu J (2016) Fruit classification by biogeography-based optimization and feedforward neural network. Expert Syst 33(3):239–253
    • (2016) Expert Syst , vol.33 , Issue.3 , pp. 239-253
    • Wu, J.1
  • 58
    • 84973547836 scopus 로고    scopus 로고
    • Dual-tree complex wavelet transform and twin support vector machine for pathological brain detection
    • Yang M (2016) Dual-tree complex wavelet transform and twin support vector machine for pathological brain detection. Appl Sci 6(6). doi:10.3390/app6060169
    • (2016) Appl Sci , vol.6 , Issue.6
    • Yang, M.1
  • 59
    • 77955735474 scopus 로고    scopus 로고
    • Daily outflow prediction by multi layer perceptron with logistic sigmoid and tangent sigmoid activation functions
    • Zadeh MR et al (2010) Daily outflow prediction by multi layer perceptron with logistic sigmoid and tangent sigmoid activation functions. Water Resour Manag 24(11):2673–2688
    • (2010) Water Resour Manag , vol.24 , Issue.11 , pp. 2673-2688
    • Zadeh, M.R.1
  • 60
    • 84960412456 scopus 로고    scopus 로고
    • Approximation of multivariate 2 pi-periodic functions by multiple 2 pi-periodic approximate identity neural networks based on the universal approximation theorems
    • Zhangjiajie, Peoples R China: IEEE
    • Zainuddin Z, Fard SP (2015) Approximation of multivariate 2 pi-periodic functions by multiple 2 pi-periodic approximate identity neural networks based on the universal approximation theorems. in 11th International Conference on Natural Computation (ICNC). Zhangjiajie, Peoples R China: IEEE pp 8–13
    • (2015) 11Th International Conference on Natural Computation (ICNC) , pp. 8-13
    • Zainuddin, Z.1    Fard, S.P.2
  • 61
    • 84986204866 scopus 로고    scopus 로고
    • Pathological brain detection by artificial intelligence in magnetic resonance imaging scanning
    • Zhan T (2016) Pathological brain detection by artificial intelligence in magnetic resonance imaging scanning. Prog Electromagn Res 156:105–133
    • (2016) Prog Electromagn Res , vol.156 , pp. 105-133
    • Zhan, T.1
  • 62
    • 85013218686 scopus 로고    scopus 로고
    • Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression
    • Zhan TM, Chen Y (2016) Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression. IEEE Access 4:7567–7576
    • (2016) IEEE Access , vol.4 , pp. 7567-7576
    • Zhan, T.M.1    Chen, Y.2
  • 63
    • 84994519388 scopus 로고    scopus 로고
    • GroRec: A Group-centric Intelligent Recommender System Integrating Social, Mobile and Big Data Technologies
    • Zhang Y (2016) GroRec: a Group-centric Intelligent Recommender System Integrating Social, Mobile and Big Data Technologies. IEEE Trans Serv Comput:1–15
    • (2016) IEEE Trans Serv Comput , pp. 1-15
    • Zhang, Y.1
  • 64
    • 84905054847 scopus 로고    scopus 로고
    • CAP: community activity prediction based on big data analysis
    • Zhang Y et al (2014) CAP: community activity prediction based on big data analysis. IEEE Netw 28(4):52–57
    • (2014) IEEE Netw , vol.28 , Issue.4 , pp. 52-57
    • Zhang, Y.1
  • 65
    • 84983643507 scopus 로고    scopus 로고
    • Health-CPS: healthcare cyber-physical system assisted by cloud and big data
    • Zhang Y et al (2015a) Health-CPS: healthcare cyber-physical system assisted by cloud and big data. IEEE Systems Journal 99:1–8
    • (2015) IEEE Systems Journal , vol.99 , pp. 1-8
    • Zhang, Y.1
  • 66
    • 84930180395 scopus 로고    scopus 로고
    • CADRE: cloud-assisted drug recommendation service for online pharmacies
    • Zhang Y et al (2015b) CADRE: cloud-assisted drug recommendation service for online pharmacies. Mobile Networks & Applications 20(3):348–355
    • (2015) Mobile Networks & Applications , vol.20 , Issue.3 , pp. 348-355
    • Zhang, Y.1
  • 67
    • 84944456448 scopus 로고    scopus 로고
    • Detection of pathological brain in MRI scanning based on wavelet-entropy and naive Bayes classifier
    • Springer International Publishing
    • Zhou X et al (2015) Detection of pathological brain in MRI scanning based on wavelet-entropy and naive Bayes classifier. In Bioinformatics and biomedical engineering. Granada, Spain: Springer International Publishing. pp. 201–209
    • (2015) Bioinformatics and Biomedical Engineering. Granada, Spain , pp. 201-209
    • Zhou, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.