11
TÍTULO: Improving deep neural network performance by reusing features trained with transductive transference
AUTORES: Kandaswamy, C; Silva, LM ; Alexandre, LA ; Santos, JM; De Sa, JM;
PUBLICAÇÃO: 2014, FONTE: 24th International Conference on Artificial Neural Networks, ICANN 2014 in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOLUME: 8681 LNCS
INDEXADO EM: Scopus
12
TÍTULO: Improving deep neural network performance by reusing features trained with transductive transference
AUTORES: Kandaswamy, C ; Silva, LM ; Alexandre, LA; Santos, JM; De Sá, JM;
PUBLICAÇÃO: 2014, FONTE: 24th International Conference on Artificial Neural Networks, ICANN 2014 in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOLUME: 8681 LNCS
INDEXADO EM: Scopus CrossRef: 10
13
TÍTULO: Improving Performance on Problems with Few Labelled Data by Reusing Stacked Auto-Encoders
AUTORES: Amaral, T; Kandaswamy, C; Silva, LM ; Alexandre, LA; de Sa, JM; Santos, JM;
PUBLICAÇÃO: 2014, FONTE: 13th International Conference on Machine Learning and Applications (ICMLA) in 2014 13TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA)
INDEXADO EM: Scopus WOS
14
TÍTULO: Improving performance on problems with few labelled data by reusing stacked auto-encoders
AUTORES: Amaral, T; Kandaswamy, C; Silva, LM ; Alexandre, LA ; Sa, JMD; Santos, JM;
PUBLICAÇÃO: 2014, FONTE: 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014 in Proceedings - 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014
INDEXADO EM: Scopus CrossRef
15
TÍTULO: Improving Transfer Learning Accuracy by Reusing Stacked Denoising Autoencoders  Full Text
AUTORES: Kandaswamy, C; Silva, LM ; Alexandre, LA ; Sousa, R; Santos, JM; de Sa, JM;
PUBLICAÇÃO: 2014, FONTE: IEEE International Conference on Systems, Man, and Cybernetics (SMC) in 2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), VOLUME: 2014-January, NÚMERO: January
INDEXADO EM: Scopus WOS CrossRef
16
TÍTULO: Transfer Learning Using Rotated Image Data to Improve Deep Neural Network Performance
AUTORES: Telmo Amaral; Luis M Silva ; Luis A Alexandre ; Chetak Kandaswamy; Joaquim Marques de Sa; Jorge M Santos;
PUBLICAÇÃO: 2014, FONTE: 11th International Conference on Image Analysis and Recognition (ICIAR) in IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT I, VOLUME: 8814
INDEXADO EM: Scopus WOS CrossRef
17
TÍTULO: Application of Artificial Neural Networks to Predict the Impact of Traffic Emissions on Human Health
AUTORES: Tania Fontes ; Luis M Silva ; Sergio R Pereira; Margarida C Coelho ;
PUBLICAÇÃO: 2013, FONTE: 16th Portuguese Conference on Artificial Intelligence (EPIA) in PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2013, VOLUME: 8154
INDEXADO EM: Scopus WOS CrossRef: 5
18
TÍTULO: Minimum error entropy classification
AUTORES: Marques De Sa, JP; Silva, LMA ; Santos, JMF; Alexandre, LA ;
PUBLICAÇÃO: 2013, FONTE: Studies in Computational Intelligence, VOLUME: 420
INDEXADO EM: Scopus CrossRef
19
TÍTULO: Using Different Cost Functions to Train Stacked Auto-encoders
AUTORES: Telmo Amaral; Luis M Silva ; Lus A Alexandre ; Chetak Kandaswamy; Jorge M Santos; Joaquim Marques de Sa;
PUBLICAÇÃO: 2013, FONTE: 12th Mexican International Conference on Artificial Intelligence (MICAI) in 2013 12TH MEXICAN INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (MICAI 2013)
INDEXADO EM: Scopus WOS CrossRef: 4
20
TÍTULO: Differential Diagnosis of Solid Pancreatic Masses. Contrast-Enhanced Harmonic Endoscopic Ultrasound, Quantitative-Elastography Endoscopic Ultrasound or Both?  Full Text
AUTORES: Julio Iglesias Garcia; Bjorn Lindkvist; Joao B Cruz Soares; Luis Miguel Silva ; Araujo Lopes; Carlos Marra Lopez; Jose Larino Noia; Enrique Dominguez Munoz;
PUBLICAÇÃO: 2012, FONTE: Digestive Disease Week (DDW) in GASTROINTESTINAL ENDOSCOPY, VOLUME: 75, NÚMERO: 4
INDEXADO EM: WOS
Página 2 de 3. Total de resultados: 29.