| Improving electric energy consumption prediction using CNN and Bi-LSTM T Le, MT Vo, B Vo, E Hwang, S Rho, SW Baik Applied Sciences 9 (20), 4237, 2019 | 264 | 2019 |
| A Novel Framework for Trash Classification Using Deep Transfer Learning AH Vo, HS Le, MT Vo, T Le IEEE Access 7, 178631-178639, 2019 | 210 | 2019 |
| Oversampling techniques for bankruptcy prediction: Novel features from a transaction dataset T Le, MY Lee, JR Park, SW Baik Symmetry 10 (4), 79, 2018 | 104 | 2018 |
| A hybrid approach using oversampling technique and cost‐sensitive learning for bankruptcy prediction T Le, MT Vo, B Vo, MY Lee, SW Baik Complexity 2019 (1), 8460934, 2019 | 100 | 2019 |
| Mining frequent itemsets using the N-list and subsume concepts B Vo, T Le, F Coenen, TP Hong International Journal of Machine Learning and Cybernetics 7, 253-265, 2016 | 98 | 2016 |
| A Cluster-Based Boosting Algorithm for Bankruptcy Prediction in a Highly Imbalanced Dataset T Le, HS Le, MT Vo, MY Lee, SW Baik Symmetry 10 (7), 250, 2018 | 97 | 2018 |
| Dealing with the Class Imbalance Problem in the Detection of Fake Job Descriptions MT Vo, AH Vo, T Nguyen, R Sharma, T Le Computers, Materials & Continua 68 (1), 521-535, 2021 | 78 | 2021 |
| Multiple electric energy consumption forecasting using a cluster-based strategy for transfer learning in smart building T Le, MT Vo, T Kieu, E Hwang, S Rho, SW Baik Sensors 20 (9), 2668, 2020 | 78 | 2020 |
| Crime rate detection using social media of different crime locations and Twitter part-of-speech tagger with Brown clustering T Vo, R Sharma, R Kumar, LH Son, BT Pham, D Tien Bui, I Priyadarshini, ... Journal of Intelligent & Fuzzy Systems 38 (4), 4287-4299, 2020 | 76 | 2020 |
| MEI: an efficient algorithm for mining erasable itemsets T Le, B Vo Engineering Applications of Artificial Intelligence 27, 155-166, 2014 | 74 | 2014 |
| A fast and accurate approach for bankruptcy forecasting using squared logistics loss with GPU-based extreme gradient boosting T Le, B Vo, H Fujita, NT Nguyen, SW Baik Information Sciences 494, 294-310, 2019 | 67 | 2019 |
| A Novel Approach for Mining Maximal Frequent Patterns B Vo, S Pham, T Le, ZH Deng Expert Systems with Applications 73, 178-186, 2017 | 65 | 2017 |
| An efficient algorithm for mining erasable itemsets using the difference of NC-Sets T Le, B Vo, F Coenen 2013 IEEE International conference on systems, man, and cybernetics, 2270-2274, 2013 | 65 | 2013 |
| An N-list-based algorithm for mining frequent closed patterns T Le, B Vo Expert Systems with Applications 42 (19), 6648-6657, 2015 | 63 | 2015 |
| An efficient and effective algorithm for mining top-rank-k frequent patterns Q Huynh-Thi-Le, T Le, B Vo, B Le Expert Systems with Applications 42 (1), 156-164, 2015 | 63 | 2015 |
| Brent Oil Price Prediction Using Bi-LSTM Network AH Vo, T Nguyen, T Le Intelligent Automation and Soft Computing 26 (6), 1307–1317, 2020 | 46 | 2020 |
| Optimization strategies of neural networks for impact damage classification of RC panels in a small dataset QH Doan, T Le, DK Thai Applied Soft Computing 102, 107100, 2021 | 45 | 2021 |
| A robust framework for self-care problem identification for children with disability T Le, SW Baik Symmetry 11 (1), 89, 2019 | 42 | 2019 |
| Mining top-k co-occurrence items with sequential pattern T Kieu, B Vo, T Le, ZH Deng, B Le Expert Systems with Applications 85, 123-133, 2017 | 41 | 2017 |
| Mining erasable itemsets with subset and superset itemset constraints B Vo, T Le, W Pedrycz, G Nguyen, SW Baik Expert Systems with Applications 69, 50-61, 2017 | 41 | 2017 |