Chetak Kandaswamy

According to our database, Chetak Kandaswamy authored at least 10 papers between 2013 and 2017.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2017

Multi-source deep transfer learning for cross-sensor biometrics.

Chetak Kandaswamy, João C. Monteiro, Luís M. Silva, Jaime S. Cardoso

Neural Comput. Appl., 2017

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

2016

Contributions on Deep Transfer Learning

Chetak Kandaswamy

PhD thesis, 2016

2015

Deep Transfer Learning Ensemble for Classification.

Chetak Kandaswamy, Luís M. Silva, Luís A. Alexandre, Jorge M. Santos

Proceedings of the Advances in Computational Intelligence, 2015

Source-Target-Source Classification Using Stacked Denoising Autoencoders.

Chetak Kandaswamy, Luís M. Silva, Jaime S. Cardoso

Proceedings of the Pattern Recognition and Image Analysis - 7th Iberian Conference, 2015

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

Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 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

Proceedings of the 13th International Conference on Machine Learning and Applications, 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

Proceedings of the Image Analysis and Recognition - 11th International Conference, 2014

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

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

2013

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

Proceedings of the 12th Mexican International Conference on Artificial Intelligence, 2013