| Convolutional radio modulation recognition networks TJ O’Shea, J Corgan, TC Clancy International conference on engineering applications of neural networks, 213-226, 2016 | 1336 | 2016 |
| Deep convolutional neural networks for fire detection in images J Sharma, OC Granmo, M Goodwin, JT Fidje International conference on engineering applications of neural networks, 183-193, 2017 | 228 | 2017 |
| Using the support vector machine as a classification method for software defect prediction with static code metrics D Gray, D Bowes, N Davey, Y Sun, B Christianson International Conference on Engineering Applications of Neural Networks, 223-234, 2009 | 122 | 2009 |
| Two hidden layers are usually better than one AJ Thomas, M Petridis, SD Walters, SM Gheytassi, RE Morgan International conference on engineering applications of neural networks, 279-290, 2017 | 98 | 2017 |
| A spiking one-class anomaly detection framework for cyber-security on industrial control systems K Demertzis, L Iliadis, S Spartalis International Conference on Engineering Applications of Neural Networks, 122-134, 2017 | 74 | 2017 |
| Multimodal data fusion for person-independent, continuous estimation of pain intensity M Kächele, P Thiam, M Amirian, P Werner, S Walter, F Schwenker, ... International Conference on Engineering Applications of Neural Networks, 275-285, 2015 | 70 | 2015 |
| Evaluating sentiment in annual reports for financial distress prediction using neural networks and support vector machines P Hájek, V Olej International Conference on Engineering Applications of Neural Networks, 1-10, 2013 | 62 | 2013 |
| A random forest method to detect Parkinson’s disease via gait analysis K Açıcı, ÇB Erdaş, T Aşuroğlu, MK Toprak, H Erdem, H Oğul International conference on engineering applications of neural networks, 609-619, 2017 | 56 | 2017 |
| Combining LSTM and feed forward neural networks for conditional rhythm composition D Makris, M Kaliakatsos-Papakostas, I Karydis, KL Kermanidis International conference on engineering applications of neural networks, 570-582, 2017 | 56 | 2017 |
| Recognizing emotion presence in natural language sentences I Perikos, I Hatzilygeroudis International conference on engineering applications of neural networks, 30-39, 2013 | 51 | 2013 |
| A recurrent neural network approach for predicting glucose concentration in type-1 diabetic patients F Allam, Z Nossai, H Gomma, I Ibrahim, M Abdelsalam Engineering applications of neural networks, 254-259, 2011 | 51 | 2011 |
| Assessment of parkinson’s disease based on deep neural networks A Tagaris, D Kollias, A Stafylopatis International Conference on Engineering Applications of Neural Networks, 391-403, 2017 | 49 | 2017 |
| Stock price movements classification using machine and deep learning techniques-the case study of indian stock market N Naik, BR Mohan International Conference on Engineering Applications of Neural Networks, 445-452, 2019 | 47 | 2019 |
| Categorization and construction of rule based systems H Liu, A Gegov, F Stahl International conference on engineering applications of neural networks, 183-194, 2014 | 46 | 2014 |
| Signal2vec: time series embedding representation C Nalmpantis, D Vrakas International Conference on Engineering Applications of Neural Networks, 80-90, 2019 | 41 | 2019 |
| Baby cry sound detection: A comparison of hand crafted features and deep learning approach R Torres, D Battaglino, L Lepauloux International Conference on Engineering Applications of Neural Networks, 168-179, 2017 | 38 | 2017 |
| Evaluating the impact of categorical data encoding and scaling on neural network classification performance: the case of repeat consumption of identical cultural goods E Fitkov-Norris, S Vahid, C Hand International Conference on Engineering Applications of Neural Networks, 343-352, 2012 | 38 | 2012 |
| Method for training a spiking neuron to associate input-output spike trains A Mohemmed, S Schliebs, S Matsuda, N Kasabov Engineering Applications of Neural Networks, 219-228, 2011 | 37 | 2011 |
| Anomaly detection from network logs using diffusion maps T Sipola, A Juvonen, J Lehtonen Engineering Applications of Neural Networks, 172-181, 2011 | 36 | 2011 |
| Predicting student performance in distance higher education using active learning G Kostopoulos, AD Lipitakis, S Kotsiantis, G Gravvanis International conference on engineering applications of neural networks, 75-86, 2017 | 35 | 2017 |
