| Spectrogram based multi-task audio classification Y Zeng, H Mao, D Peng, Z Yi Multimedia Tools and Applications 78, 3705-3722, 2019 | 161 | 2019 |
| Cell tracking using deep neural networks with multi-task learning T He, H Mao, J Guo, Z Yi Image and Vision Computing 60, 142-153, 2017 | 89 | 2017 |
| Protein secondary structure prediction by using deep learning method Y Wang, H Mao, Z Yi Knowledge-Based Systems 118, 115-123, 2017 | 86 | 2017 |
| Learning probabilistic automata for model checking H Mao, Y Chen, M Jaeger, TD Nielsen, KG Larsen, B Nielsen 2011 Eighth International Conference on Quantitative Evaluation of Systems …, 2011 | 66 | 2011 |
| Learning deterministic probabilistic automata from a model checking perspective H Mao, Y Chen, M Jaeger, TD Nielsen, KG Larsen, B Nielsen Machine Learning 105, 255-299, 2016 | 60 | 2016 |
| Audio classification using attention-augmented convolutional neural network Y Wu, H Mao, Z Yi Knowledge-Based Systems 161, 90-100, 2018 | 50 | 2018 |
| Learning Markov decision processes for model checking H Mao, Y Chen, M Jaeger, TD Nielsen, KG Larsen, B Nielsen arXiv preprint arXiv:1212.3873, 2012 | 46 | 2012 |
| Low-rank representation with adaptive dictionary learning for subspace clustering J Chen, H Mao, Z Wang, X Zhang Knowledge-Based Systems 223, 107053, 2021 | 43 | 2021 |
| Subspace clustering using a symmetric low-rank representation J Chen, H Mao, Y Sang, Z Yi Knowledge-Based Systems 127, 46-57, 2017 | 43 | 2017 |
| Multiview subspace clustering using low-rank representation J Chen, S Yang, H Mao, C Fahy IEEE Transactions on Cybernetics 52 (11), 12364-12378, 2021 | 37 | 2021 |
| Moving object recognition using multi-view three-dimensional convolutional neural networks T He, H Mao, Z Yi Neural computing and applications 28, 3827-3835, 2017 | 36 | 2017 |
| Cell mitosis detection using deep neural networks Y Zhou, H Mao, Z Yi Knowledge-Based Systems 137, 19-28, 2017 | 30 | 2017 |
| Symmetric low-rank representation for subspace clustering J Chen, H Zhang, H Mao, Y Sang, Z Yi Neurocomputing 173, 1192-1202, 2016 | 29 | 2016 |
| Learning Markov models for stationary system behaviors Y Chen, H Mao, M Jaeger, TD Nielsen, K Guldstrand Larsen, B Nielsen NASA Formal Methods: 4th International Symposium, NFM 2012, Norfolk, VA, USA …, 2012 | 25 | 2012 |
| Utilizing partial policies for identifying equivalence of behavioral models Y Zeng, P Doshi, Y Pan, H Mao, M Chandrasekaran, J Luo Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 1083-1088, 2011 | 24 | 2011 |
| Stem cell motion-tracking by using deep neural networks with multi-output Y Wang, H Mao, Z Yi Neural Computing and Applications 31, 3455-3467, 2019 | 21 | 2019 |
| Improved use of partial policies for identifying behavioral equivalence. Y Zeng, H Mao, Y Pan, J Luo AAMAS, 1015-1022, 2012 | 19 | 2012 |
| Explicit guiding auto-encoders for learning meaningful representation Y Sun, H Mao, Y Sang, Z Yi Neural computing and applications 28, 429-436, 2017 | 17 | 2017 |
| Efficient sparse representation for learning with high-dimensional data J Chen, S Yang, Z Wang, H Mao IEEE Transactions on Neural Networks and Learning Systems 34 (8), 4208-4222, 2021 | 10 | 2021 |
| Symmetric low-rank preserving projections for subspace learning J Chen, H Mao, H Zhang, Z Yi Neurocomputing 315, 381-393, 2018 | 10 | 2018 |
