| High-content analysis of breast cancer using single-cell deep transfer learning C Kandaswamy, LM Silva, LA Alexandre, JM Santos Journal of biomolecular screening 21 (3), 252-259, 2016 | 80 | 2016 |
| Using different cost functions to train stacked auto-encoders T Amaral, LM Silva, LA Alexandre, C Kandaswamy, JM Santos, JM de Sá Mexican International Conference on Artificial Intelligence (MICAI), 2013 …, 2013 | 64 | 2013 |
| Improving deep neural network performance by reusing features trained with transductive transference C Kandaswamy, LM Silva, LA Alexandre, JM Santos, JM de Sá International Conference on Artificial Neural Networks, 265-272, 2014 | 54 | 2014 |
| Improving transfer learning accuracy by reusing stacked denoising autoencoders C Kandaswamy, LM Silva, LA Alexandre, R Sousa, JM Santos, JM de Sá International Conference on Systems, Man, and Cybernetics (SMC), 1380-1387, 2014 | 49 | 2014 |
| Multi-source deep transfer learning for cross-sensor biometrics C Kandaswamy, JC Monteiro, LM Silva, JS Cardoso Neural Computing and Applications 28 (9), 2461-2475, 2017 | 30 | 2017 |
| Speedup of deep learning ensembles for semantic segmentation using a model compression technique A Holliday, M Barekatain, J Laurmaa, C Kandaswamy, H Prendinger Computer Vision and Image Understanding 164, 16-26, 2017 | 29 | 2017 |
| Speedup of deep learning ensembles for semantic segmentation using a model compression technique A Holliday, M Barekatain, J Laurmaa, C Kandaswamy, H Prendinger Computer Vision and Image Understanding 164, 16-26, 2017 | 29 | 2017 |
| Transfer learning using rotated image data to improve deep neural network performance T Amaral, LM Silva, LA Alexandre, C Kandaswamy, JM de Sá, JM Santos International Conference Image Analysis and Recognition, 290-300, 2014 | 28 | 2014 |
| Deep Transfer Learning Ensemble for Classification C Kandaswamy, LM Silva, LA Alexandre, JM Santos International Work-Conference on Artificial Neural Networks, 335-348, 2015 | 19 | 2015 |
| Improving performance on problems with few labelled data by reusing stacked auto-encoders T Amaral, C Kandaswamy, LM Silva, LA Alexandre, J Marques De Sa, ... Machine Learning and Applications (ICMLA), 2014 13th International …, 2014 | 16 | 2014 |
| Transfer Learning: Current Status, Trends and Challenges R Sousa, LM Silva, LA Alexandre, J Santos, JM De Sá 20th Portuguese Conference on Pattern Recognition, RecPad, 57-58, 2014 | 12 | 2014 |
| Source-target-source classification using stacked denoising autoencoders C Kandaswamy, LM Silva, JS Cardoso Iberian Conference on Pattern Recognition and Image Analysis, 39-47, 2015 | 8 | 2015 |
| Tuning parameters of deep neural network algorithms for identifying best cost function C Kandaswamy, T Amaral Technical Report 2/2013, Instituto de Engenharia Biomédica/NNIG, 2013 | 4 | 2013 |
| Luıs. Alexandre, Ricardo Sousa, JM Santos, and J. Marques de Sá. Improving Transfer Learning Accuracy by Reusing Stacked Denoising Autoencoders. Systems Man and Cybernetics C Kandaswamy, L Silva IEEE Conference on. IEEE, 2014 | 2 | 2014 |
| Report: Improving CNN by Reusing Features Trained with Transductive Transfer Setting C Kandaswamy, L Silva, L Alexandre Technical Report 2/2014, Instituto de Engenharia Biomedica/NNIG, Febyrary …, 0 | 1 | |
| Contributions on Deep Transfer Learning C Kandaswamy | | 2016 |
| Activities report from March 2014 to March 2015 C Kandaswamy | | 2015 |
| Improve Performance in Deep Neural Networks:(1) Cost Functions, and (2) Reusable learning C Kandaswamy | | 2014 |
| Deep Transfer Learning Ensemble for Classification C Kandaswamy123, LM Silva24, LA Alexandre, JM Santos26 | | |
| Oral Sessions: Pattern Recognition and Machine Learning A González, D Vázquez, S Ramos, AM López, J Amores, EM Pereira, ... | | |
Luís AlexandreUniversidade da Beira Interior, PortugalVerified email at ubi.pt
