| A survey of deep neural network architectures and their applications W Liu, Z Wang, X Liu, N Zeng, Y Liu, FE Alsaadi Neurocomputing 234, 11-26, 2017 | 3863 | 2017 |
| Identification of rice diseases using deep convolutional neural networks Y Lu, S Yi, N Zeng, Y Liu, Y Zhang Neurocomputing 267, 378-384, 2017 | 1101 | 2017 |
| Facial expression recognition via learning deep sparse autoencoders N Zeng, H Zhang, B Song, W Liu, Y Li, AM Dobaie Neurocomputing 273, 643-649, 2018 | 575 | 2018 |
| A small-sized object detection oriented multi-scale feature fusion approach with application to defect detection N Zeng, P Wu, Z Wang, H Li, W Liu, X Liu IEEE Transactions on Instrumentation and Measurement 71, 1-14, 2022 | 441 | 2022 |
| A review on transfer learning in EEG signal analysis Z Wan, R Yang, M Huang, N Zeng, X Liu Neurocomputing 421, 1-14, 2021 | 428 | 2021 |
| A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer’s disease N Zeng, H Qiu, Z Wang, W Liu, H Zhang, Y Li Neurocomputing 320, 195-202, 2018 | 317 | 2018 |
| A novel sigmoid-function-based adaptive weighted particle swarm optimizer W Liu, Z Wang, Y Yuan, N Zeng, K Hone, X Liu IEEE Transactions on Cybernetics 51 (2), 1085-1093, 2019 | 306 | 2019 |
| Position-transitional particle swarm optimization-incorporated latent factor analysis X Luo, Y Yuan, S Chen, N Zeng, Z Wang IEEE Transactions on Knowledge and Data Engineering 34 (8), 3958-3970, 2020 | 284 | 2020 |
| A dynamic neighborhood-based switching particle swarm optimization algorithm N Zeng, Z Wang, W Liu, H Zhang, K Hone, X Liu IEEE transactions on cybernetics 52 (9), 9290-9301, 2020 | 258 | 2020 |
| Generative adversarial networks and its applications in biomedical informatics L Lan, L You, Z Zhang, Z Fan, W Zhao, N Zeng, Y Chen, X Zhou Frontiers in Public Health 8, 164, 2020 | 240 | 2020 |
| A fast fractal based compression for MRI images S Liu, W Bai, N Zeng, S Wang IEEE Access 7, 62412-62420, 2019 | 235 | 2019 |
| A switching delayed PSO optimized extreme learning machine for short-term load forecasting N Zeng, H Zhang, W Liu, J Liang, FE Alsaadi Neurocomputing 240, 175-182, 2017 | 226 | 2017 |
| Deep belief networks for quantitative analysis of a gold immunochromatographic strip N Zeng, Z Wang, H Zhang, W Liu, FE Alsaadi Cognitive Computation 8, 684-692, 2016 | 169 | 2016 |
| An improved particle filter with a novel hybrid proposal distribution for quantitative analysis of gold immunochromatographic strips N Zeng, Z Wang, H Zhang, KE Kim, Y Li, X Liu IEEE Transactions on Nanotechnology 18, 819-829, 2019 | 163 | 2019 |
| A novel particle swarm optimization approach for patient clustering from emergency departments W Liu, Z Wang, X Liu, N Zeng, D Bell IEEE Transactions on Evolutionary Computation 23 (4), 632-644, 2018 | 162 | 2018 |
| FMD-Yolo: An efficient face mask detection method for COVID-19 prevention and control in public P Wu, H Li, N Zeng, F Li Image and Vision Computing 117, 104341, 2022 | 156 | 2022 |
| Image-based quantitative analysis of gold immunochromatographic strip via cellular neural network approach N Zeng, Z Wang, B Zineddin, Y Li, M Du, L Xiao, X Liu, T Young IEEE Transactions on Medical Imaging 33 (5), 1129-1136, 2014 | 154 | 2014 |
| A novel switching delayed PSO algorithm for estimating unknown parameters of lateral flow immunoassay N Zeng, Z Wang, H Zhang, FE Alsaadi Cognitive Computation 8, 143-152, 2016 | 146 | 2016 |
| Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip N Zeng, H Li, Z Wang, W Liu, S Liu, FE Alsaadi, X Liu Neurocomputing 425, 173-180, 2021 | 145 | 2021 |
| Predicting Alzheimer’s disease using LSTM X Hong, R Lin, C Yang, N Zeng, C Cai, J Gou, J Yang IEEE Access 7, 80893-80901, 2019 | 134 | 2019 |
Zidong WangChair Professor, MAE, MEASA, FIEEE, Brunel University London, UKVerifisert e-postadresse på brunel.ac.uk
