Using Different Cost Functions to Train Stacked Auto-Encoders. - Telmo Amaral; Luís M. Silva; Luís A. Alexandre; Chetak Kandaswamy; Jorge M. Santos; Joaquim Marques de Sá (MICAI (Special Sessions), 2013)

Improving Deep Neural Network Performance by Reusing Features Trained with Transductive Transference. - Chetak Kandaswamy; Luís M. Silva; Luís A. Alexandre; Jorge M. Santos; Joaquim Marques de Sá (ICANN, 2014)

Transfer Learning Using Rotated Image Data to Improve Deep Neural Network Performance. - Telmo Amaral; Luís M. Silva; Luís A. Alexandre; Chetak Kandaswamy; Joaquim Marques de Sá; Jorge M. Santos (ICIAR (1), 2014)

Improving Performance on Problems with Few Labelled Data by Reusing Stacked Auto-Encoders. - Telmo Amaral; Chetak Kandaswamy; Luís M. Silva; Luís A. Alexandre; Joaquim Marques de Sá; Jorge M. Santos (ICMLA, 2014)

Improving transfer learning accuracy by reusing Stacked Denoising Autoencoders. - Chetak Kandaswamy; Luís M. Silva; Luís A. Alexandre; Ricardo Gamelas Sousa; Jorge M. Santos; Joaquim Marques de Sá (SMC, 2014)

Source-Target-Source Classification Using Stacked Denoising Autoencoders. - Chetak Kandaswamy; Luís M. Silva; Jaime S. Cardoso 001 (IbPRIA, 2015)

Deep Transfer Learning Ensemble for Classification. - Chetak Kandaswamy; Luís M. Silva; Luís A. Alexandre; Jorge M. Santos (IWANN (1), 2015)

Contributions on Deep Transfer Learning - Chetak Kandaswamy (2016)

Speedup of deep learning ensembles for semantic segmentation using a model compression technique. - Andrew Holliday; Mohammadamin Barekatain; Johannes Laurmaa; Chetak Kandaswamy; Helmut Prendinger (Comput. Vis. Image Underst., 2017)

Multi-source deep transfer learning for cross-sensor biometrics. - Chetak Kandaswamy; João C. Monteiro; Luís M. Silva; Jaime S. Cardoso 001 (Neural Comput. Appl., 2017)