Publications

Found 18 results
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Vidács L, Dévai R, Ferenc R, Gyimóthy T.  2012.  Developer Support for Understanding Preprocessor Macro Expansions. Proceedings of International Conference on Advanced Software Engineering & Its Applications (ASEA 2012). 340:121-130.
T
Tóth L, Kocsor A, Kovács K.  2000.  A Discriminative Segmental Speech Model and its Application to Hungarian Number Recognition. Text, Speech and Dialogue: Third International Workshop, TSD 2000, LNAI vol. 1902. :307-313.
Thury A., Kókai G., Csirik J., Gyimóthy T, Csanády M..  1998.  Development of SPECG System for Automated ECG Analysis. XXVth International Congress on Electrocardiology and 39th International Vectorcardiography. :37.
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Szőke G, Nagy C, Hegedüs P, Ferenc R, Gyimóthy T.  2015.  Do Automatic Refactorings Improve Maintainability? An Industrial Case Study Proceedings of the 31st International Conference on Software Maintenance and Evolution – ICSME'15. :429–438.
Szilágyi G., Harmath L., Gyimóthy T..  2001.  The Debug slicing of logic programs. Acta Cybernetica. 15:257–278.
J
Jiang X., Abegglen K., Bunke H., Csirik J.  2003.  Dynamic computation of generalised median strings. Pattern Analysis & Applications. 6:185–193.
Jiang X., Abegglen K., Bunke H., Csirik J.  2003.  Dynamic Computation of Generalised Median Strings. Pattern Anal. Appl.. 6:185–193.
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Hegedűs I, Danner G, Jelasity M.  2020.  Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning. Machine Learning and Knowledge Discovery in Databases. :317–332.
Harmath L., Szilágyi G., Gyimóthy T, Csirik J..  1999.  Dynamic Slicing of Logic Programs: Program analysis and verification. The Sixth Fenno-Ugric Symposium on Software Technology. :101-113.
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Gosztolya G, Busa-Fekete R, Grósz T, Tóth L.  2017.  DNN-Based Feature Extraction and Classifier Combination for Child-Directed Speech, Cold and Snoring Identification. Proceedings of Interspeech. :3522–3526.
Gosztolya G, Tóth L.  2017.  DNN-based Feature Extraction for Conflict Intensity Estimation from Speech. IEEE Signal Processing Letters. 24:1837–1841.
Gergely T, Balogh G, Horvath F, Vancsics B, Beszedes A, Gyimothy T.  2019.  Differences between a static and a dynamic test-to-code traceability recovery method. SOFTWARE QUALITY JOURNAL. 27:797-822.
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Ferenc R., Beszedes A..  2002.  Data exchange with the columbus schema for c++. Proceedings of the Sixth European Conference on Software Maintenance and Reengineering. :59-66.
Ferenc R, Viszkok T, Aladics T, Jász J, Hegedűs P.  2020.  Deep-water framework: The Swiss army knife of humans working with machine learning models. SoftwareX. 12:100551.
Faragó C, Hegedüs P.  2018.  Developer Focus: Lack of Impact on Maintainability. Proceedings of the International Conference on Computational Science and Its Applications – ICCSA 2018. 10964:391–402.
C
Csapó TGábor, Grósz T, Gosztolya G, Tóth L, Markó A.  2017.  DNN-Based Ultrasound-to-Speech Conversion for a Silent Speech Interface. Proceedings of Interspeech. :3672–3676.
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Blázsik Z., Holló C., Imreh B..  1998.  On Decision-mappings Related to Process Network Synthesis Problem. Acta Cybern.. 13:319–328.
Berta Á, Jelasity M.  2017.  Decentralized management of random walks over a mobile phone network.. Proceedings of the 25th Euromicro Conference on Parallel, Distributed and Network-Based Processing. :100–107.