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György Kovács 0001
Person information
- affiliation: Luleå University of Technology, Embedded Internet Systems Lab, Sweden
- affiliation (PhD 2018): University of Szeged, Research Group on Artificial Intelligence, Hungarian Academy of Sciences, Hungary
Other persons with the same name
- György Kovács — disambiguation page
- György Kovács 0002
— Analytical Minds Ltd., Hungary (and 1 more)
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2020 – today
- 2024
- [j7]Aleksis Pirinen, Nosheen Abid
, Nuria Agues Paszkowsky, Thomas Ohlson Timoudas, Ronald Scheirer
, Chiara Ceccobello
, György Kovács
, Anders Persson:
Creating and Leveraging a Synthetic Dataset of Cloud Optical Thickness Measures for Cloud Detection in MSI. Remote. Sens. 16(4): 694 (2024) - 2023
- [c23]Sana Sabah Al-Azzawi, György Kovács, Filip Nilsson, Tosin P. Adewumi, Marcus Liwicki:
NLP-LTU at SemEval-2023 Task 10: The Impact of Data Augmentation and Semi-Supervised Learning Techniques on Text Classification Performance on an Imbalanced Dataset. SemEval@ACL 2023: 1421-1427 - [i3]Sana Sabah Al-Azzawi
, György Kovács, Filip Nilsson, Tosin P. Adewumi, Marcus Liwicki:
NLP-LTU at SemEval-2023 Task 10: The Impact of Data Augmentation and Semi-Supervised Learning Techniques on Text Classification Performance on an Imbalanced Dataset. CoRR abs/2304.12847 (2023) - [i2]Aleksis Pirinen, Nosheen Abid, Nuria Agues Paszkowsky, Thomas Ohlson Timoudas, Ronald Scheirer
, Chiara Ceccobello, György Kovács, Anders Persson:
Creating and Benchmarking a Synthetic Dataset for Cloud Optical Thickness Estimation. CoRR abs/2311.14024 (2023) - 2022
- [j6]György Kovács, Pedro Alonso, Rajkumar Saini, Marcus Liwicki:
Leveraging external resources for offensive content detection in social media. AI Commun. 35(2): 87-109 (2022) - [c22]Sumit Rakesh, Foteini Liwicki, Hamam Mokayed, Richa Upadhyay, Prakash Chandra Chhipa, Vibha Gupta, Kanjar De, György Kovács, Dinesh Singh, Rajkumar Saini:
Emotions Classification Using EEG in Health Care. CVMI 2022: 37-49 - [c21]Filip Nilsson, Sana Sabah Al-Azzawi, György Kovács:
Leveraging Sentiment Data for the Detection of Homophobic/Transphobic Content in a Multi-Task, Multi-Lingual Setting Using Transformers. FIRE (Working Notes) 2022: 196-207 - [c20]Sana Sabah Sabry, Tosin P. Adewumi, Nosheen Abid, György Kovács, Foteini Liwicki, Marcus Liwicki:
HaT5: Hate Language Identification using Text-to-Text Transfer Transformer. IJCNN 2022: 1-7 - [c19]Filip Nilsson, György Kovács:
FilipN@LT-EDI-ACL2022-Detecting signs of Depression from Social Media: Examining the use of summarization methods as data augmentation for text classification. LT-EDI 2022: 283-286 - [i1]Sana Sabah Sabry, Tosin P. Adewumi, Nosheen Abid, György Kovács, Foteini Liwicki, Marcus Liwicki:
HaT5: Hate Language Identification using Text-to-Text Transfer Transformer. CoRR abs/2202.05690 (2022) - 2021
- [j5]Nosheen Abid, Muhammad Shahzad, Muhammad Imran Malik, Ulrich Schwanecke, Adrian Ulges, György Kovács, Faisal Shafait:
UCL: Unsupervised Curriculum Learning for water body classification from remote sensing imagery. Int. J. Appl. Earth Obs. Geoinformation 105: 102568 (2021) - [j4]György Kovács
, Pedro Alonso, Rajkumar Saini:
Challenges of Hate Speech Detection in Social Media. SN Comput. Sci. 2(2): 95 (2021) - [c18]Aya Rizk
, Cathrine F. Seidelin, György Kovács, Marcus Liwicki, Rickard Brännvall
:
Defining Beneficiaries of Emerging Data Infrastructures Towards Effective Data Appropriation - Insights from the Swedish Space Data Lab. ICIST 2021: 32-47 - 2020
- [c17]György Kovács, Rickard Brännvall, Johan Öhman, Marcus Liwicki:
Cross-Encoded Meta Embedding towards Transfer Learning. ESANN 2020: 631-636 - [c16]Pedro Alonso, Rajkumar Saini, György Kovács:
TheNorth at SemEval-2020 Task 12: Hate Speech Detection Using RoBERTa. SemEval@COLING 2020: 2197-2202 - [c15]Pedro Alonso, Rajkumar Saini, György Kovács:
Hate Speech Detection Using Transformer Ensembles on the HASOC Dataset. SPECOM 2020: 13-21
2010 – 2019
- 2019
- [c14]György Kovács, Vanda Balogh, Purvanshi Mehta, Kumar Shridhar, Pedro Alonso, Marcus Liwicki:
Author Profiling using Semantic and Syntactic Features. CLEF (Working Notes) 2019 - [c13]Pedro Alonso, Rajkumar Saini, György Kovács:
TheNorth at HASOC 2019: Hate Speech Detection in Social Media Data. FIRE (Working Notes) 2019: 293-299 - [c12]Kumar Shridhar, Ayushman Dash, Amit Sahu, Gustav Grund Pihlgren
, Pedro Alonso, Vinaychandran Pondenkandath, György Kovács, Foteini Simistira, Marcus Liwicki:
Subword Semantic Hashing for Intent Classification on Small Datasets. IJCNN 2019: 1-6 - [c11]György Kovács, László Tóth, Dirk Van Compernolle, Marcus Liwicki:
Examining the Combination of Multi-Band Processing and Channel Dropout for Robust Speech Recognition. INTERSPEECH 2019: 421-425 - [p1]György Kovács, Tamás Grósz, Tamás Váradi:
Using Deep Rectifier Neural Nets and Probabilistic Sampling for Topical Unit Classification. Cognitive Infocommunications, Theory and Applications 2019: 1-24 - 2018
- [b1]György Kovács:
Noise Robust Automatic Speech Recognition Based on Spectro-Temporal Techniques. University of Szeged, Hungary, 2018 - [c10]László Hunyadi, Tamás Váradi, György Kovács, István Szekrényes, Hermina Kiss, Karolina Takács:
Human-human, human-machine communication: on the HuComTech multimodal corpus. CLARIN Annual Conference 2018: 56-65 - [c9]György Kovács, László Tóth, Gábor Gosztolya:
Multi-Band Processing With Gabor Filters and Time Delay Neural Nets for Noise Robust Speech Recognition. SLT 2018: 242-249 - [c8]László Tóth, György Kovács, Dirk Van Compernolle:
A Perceptually Inspired Data Augmentation Method for Noise Robust CNN Acoustic Models. SPECOM 2018: 697-706 - [c7]György Kovács:
Classification of Formal and Informal Dialogues Based on Emotion Recognition Features. TSD 2018: 518-526 - 2017
- [j3]György Kovács, László Tóth
, Dirk Van Compernolle, Sriram Ganapathy:
Increasing the robustness of CNN acoustic models using autoregressive moving average spectrogram features and channel dropout. Pattern Recognit. Lett. 100: 44-50 (2017) - [c6]István Szekrényes, György Kovács:
Classification of Formal and Informal Dialogues Based on Turn-Taking and Intonation Using Deep Neural Networks. SPECOM 2017: 233-243 - 2016
- [c5]György Kovács, Tamás Grósz
, Tamás Váradi:
Topical unit classification using deep neural nets and probabilistic sampling. CogInfoCom 2016: 199-204 - 2015
- [j2]György Kovács, László Tóth
:
Joint Optimization of Spectro-Temporal Features and Deep Neural Nets for Robust Automatic Speech Recognition. Acta Cybern. 22(1): 117-134 (2015) - [j1]György Kovács, László Tóth
, Dirk Van Compernolle:
Selection and enhancement of Gabor filters for automatic speech recognition. Int. J. Speech Technol. 18(1): 1-16 (2015) - 2014
- [c4]György Kovács, László Tóth, Tamás Grósz:
Robust Multi-Band ASR Using Deep Neural Nets and Spectro-temporal Features. SPECOM 2014: 386-393 - 2013
- [c3]György Kovács, László Tóth
:
The Joint Optimization of Spectro-Temporal Features and Neural Net Classifiers. TSD 2013: 552-559 - 2011
- [c2]Gábor Gosztolya, György Kovács, László Tóth
:
Spoken term detection from noisy input. SACI 2011: 91-96 - [c1]György Kovács, László Tóth
:
Phone recognition experiments with 2D-DCT spectro-temporal features. SACI 2011: 143-146
Coauthor Index
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last updated on 2024-08-21 20:28 CEST by the dblp team
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