| Mixture of experts: a literature survey S Masoudnia, R Ebrahimpour Artificial Intelligence Review 42, 275-293, 2014 | 585 | 2014 |
| ECG arrhythmia recognition via a neuro-SVM–KNN hybrid classifier with virtual QRS image-based geometrical features MR Homaeinezhad, SA Atyabi, E Tavakkoli, HN Toosi, A Ghaffari, ... Expert Systems with Applications 39 (2), 2047-2058, 2012 | 199 | 2012 |
| PPIevo: Protein–protein interaction prediction from PSSM based evolutionary information J Zahiri, O Yaghoubi, M Mohammad-Noori, R Ebrahimpour, ... Genomics 102 (4), 237-242, 2013 | 164 | 2013 |
| Decentralized multi-agent based energy management of microgrid using reinforcement learning E Samadi, A Badri, R Ebrahimpour International Journal of Electrical Power & Energy Systems 122, 106211, 2020 | 141 | 2020 |
| Classification of ECG arrhythmia by a modular neural network based on mixture of experts and negatively correlated learning M Javadi, SAAA Arani, A Sajedin, R Ebrahimpour Biomedical Signal Processing and Control 8 (3), 289-296, 2013 | 140 | 2013 |
| Beyond core object recognition: Recurrent processes account for object recognition under occlusion K Rajaei, Y Mohsenzadeh, R Ebrahimpour, SM Khaligh-Razavi PLoS computational biology 15 (5), e1007001, 2019 | 120 | 2019 |
| Multiple classifier system for EEG signal classification with application to brain–computer interfaces A Ahangi, M Karamnejad, N Mohammadi, R Ebrahimpour, N Bagheri Neural Computing and Applications 23, 1319-1327, 2013 | 107 | 2013 |
| Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange R Ebrahimpour, H Nikoo, S Masoudnia, MR Yousefi, MS Ghaemi International Journal of Forecasting 27 (3), 804-816, 2011 | 84 | 2011 |
| A resource-limited hardware accelerator for convolutional neural networks in embedded vision applications S Moini, B Alizadeh, M Emad, R Ebrahimpour IEEE Transactions on Circuits and Systems II: Express Briefs 64 (10), 1217-1221, 2017 | 83 | 2017 |
| Improving ECG classification accuracy using an ensemble of neural network modules M Javadi, R Ebrahimpour, A Sajedin, S Faridi, S Zakernejad PLoS one 6 (10), e24386, 2011 | 71 | 2011 |
| New differential fault analysis on PRESENT N Bagheri, R Ebrahimpour, N Ghaedi EURASIP Journal on Advances in Signal Processing 2013, 1-10, 2013 | 69 | 2013 |
| Vanishing point detection in corridors: using Hough transform and K-means clustering R Ebrahimpour, R Rasoolinezhad, Z Hajiabolhasani, M Ebrahimi IET computer vision 6 (1), 40-51, 2012 | 66 | 2012 |
| LocFuse: human protein–protein interaction prediction via classifier fusion using protein localization information J Zahiri, M Mohammad-Noori, R Ebrahimpour, S Saadat, JH Bozorgmehr, ... Genomics 104 (6), 496-503, 2014 | 64 | 2014 |
| Feedforward object-vision models only tolerate small image variations compared to human M Ghodrati, A Farzmahdi, K Rajaei, R Ebrahimpour, SM Khaligh-Razavi Frontiers in computational neuroscience 8, 74, 2014 | 55 | 2014 |
| Predicting protein–protein interactions between human and hepatitis C virus via an ensemble learning method A Emamjomeh, B Goliaei, J Zahiri, R Ebrahimpour Molecular Biosystems 10 (12), 3147-3154, 2014 | 51 | 2014 |
| How can selection of biologically inspired features improve the performance of a robust object recognition model? M Ghodrati, SM Khaligh-Razavi, R Ebrahimpour, K Rajaei, M Pooyan PloS one 7 (2), e32357, 2012 | 51 | 2012 |
| Knitted fabric defect classification for uncertain labels based on Dempster–Shafer theory of evidence M Tabassian, R Ghaderi, R Ebrahimpour Expert Systems with Applications 38 (5), 5259-5267, 2011 | 51 | 2011 |
| View-independent face recognition with mixture of experts R Ebrahimpour, E Kabir, H Esteky, MR Yousefi Neurocomputing 71 (4-6), 1103-1107, 2008 | 47 | 2008 |
| Face detection using mixture of MLP experts R Ebrahimpour, E Kabir, MR Yousefi Neural Processing Letters 26, 69-82, 2007 | 44 | 2007 |
| Invariant object recognition is a personalized selection of invariant features in humans, not simply explained by hierarchical feed-forward vision models H Karimi-Rouzbahani, N Bagheri, R Ebrahimpour Scientific reports 7 (1), 14402, 2017 | 41 | 2017 |
Sajjad ZabbahResearch Fellow, Department of Imaging Neuroscience, University College LondonBestätigte E-Mail-Adresse bei ucl.ac.uk
