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2020 – today
- 2023
[j16]Davoud Gholamiangonabadi, Katarina Grolinger
:
Personalized models for human activity recognition with wearable sensors: deep neural networks and signal processing. Appl. Intell. 53(5): 6041-6061 (2023)- 2022
- [j15]Fadi AlMahamid, Katarina Grolinger:
Autonomous Unmanned Aerial Vehicle navigation using Reinforcement Learning: A systematic review. Eng. Appl. Artif. Intell. 115: 105321 (2022) - [j14]Khushwant Rai, Farnam Hojatpanah, Firouz Badrkhani Ajaei, Josep M. Guerrero, Katarina Grolinger:
Deep learning for high-impedance fault detection and classification: transformer-CNN. Neural Comput. Appl. 34(16): 14067-14084 (2022) - [j13]Kyle Dunphy, Mohammad Navid Fekri, Katarina Grolinger, Ayan Sadhu:
Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information. Sensors 22(16): 6193 (2022) - [c22]Fadi AlMahamid, Hanan Lutfiyya, Katarina Grolinger:
Virtual Sensor Middleware: Managing IoT Data for the Fog-Cloud Platform. CCECE 2022: 41-48 - [c21]Fadi AlMahamid, Katarina Grolinger:
Agglomerative Hierarchical Clustering with Dynamic Time Warping for Household Load Curve Clustering. CCECE 2022: 241-247 - [c20]Spencer Vecile, Kyle Lacroix, Katarina Grolinger, Jagath Samarabandu:
Malicious and Benign URL Dataset Generation Using Character-Level LSTM Models. DSC 2022: 1-8 - [c19]Sergio A. Salinas, Mohamed Ahmed T. A. Elgalhud, Luke Tambakis, Sanket Salunke, Kshitija Patel, Hamada Ghenniwa, Abdelkader Ouda, Kenneth A. McIsaac, Katarina Grolinger, Ana Luisa Trejos:
Comparison of Machine Learning Techniques for Activities of Daily Living Classification with Electromyographic Data. ICORR 2022: 1-6 - [i5]Fadi AlMahamid, Katarina Grolinger:
Autonomous Unmanned Aerial Vehicle Navigation using Reinforcement Learning: A Systematic Review. CoRR abs/2208.12328 (2022) - [i4]Fadi AlMahamid, Katarina Grolinger:
Reinforcement Learning Algorithms: An Overview and Classification. CoRR abs/2209.14940 (2022) - [i3]Fadi AlMahamid, Katarina Grolinger:
Agglomerative Hierarchical Clustering with Dynamic Time Warping for Household Load Curve Clustering. CoRR abs/2210.09523 (2022) - [i2]Fadi AlMahamid, Hanan Lutfiyya, Katarina Grolinger:
Virtual Sensor Middleware: Managing IoT Data for the Fog-Cloud Platform. CoRR abs/2210.10481 (2022) - 2021
- [j12]Rashpinder Kaur Jagait, Mohammad Navid Fekri, Katarina Grolinger, Syed Mir:
Load Forecasting Under Concept Drift: Online Ensemble Learning With Recurrent Neural Network and ARIMA. IEEE Access 9: 98992-99008 (2021) - [j11]Ananda Mohon Ghosh, Katarina Grolinger:
Edge-Cloud Computing for Internet of Things Data Analytics: Embedding Intelligence in the Edge With Deep Learning. IEEE Trans. Ind. Informatics 17(3): 2191-2200 (2021) - [c18]Fadi AlMahamid, Katarina Grolinger:
Reinforcement Learning Algorithms: An Overview and Classification. CCECE 2021: 1-7 - [i1]Khushwant Rai, Farnam Hojatpanah, Firouz Badrkhani Ajaei, Katarina Grolinger:
Deep Learning for High-Impedance Fault Detection: Convolutional Autoencoders. CoRR abs/2106.13276 (2021) - 2020
- [j10]Ljubisa Sehovac, Katarina Grolinger:
Deep Learning for Load Forecasting: Sequence to Sequence Recurrent Neural Networks With Attention. IEEE Access 8: 36411-36426 (2020) - [j9]Davoud Gholamiangonabadi, Nikita Kiselov, Katarina Grolinger:
Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection. IEEE Access 8: 133982-133994 (2020) - [c17]Yilong Yang, Nafees Qamar, Peng Liu, Katarina Grolinger, Weiru Wang, Zhi Li, Zhifang Liao:
ServeNet: A Deep Neural Network for Web Services Classification. ICWS 2020: 168-175
2010 – 2019
- 2019
- [j8]Yifang Tian, Ljubisa Sehovac, Katarina Grolinger:
Similarity-Based Chained Transfer Learning for Energy Forecasting With Big Data. IEEE Access 7: 139895-139908 (2019) - [c16]Ananda Mohon Ghosh, Katarina Grolinger:
Deep Learning: Edge-Cloud Data Analytics for IoT. CCECE 2019: 1-7 - [c15]Ljubisa Sehovac, Cornelius Nesen, Katarina Grolinger:
Forecasting Building Energy Consumption with Deep Learning: A Sequence to Sequence Approach. ICIOT 2019: 108-116 - 2018
- [j7]Dennis Bachmann, Katarina Grolinger, Hany F. ElYamany, Wilson A. Higashino, Miriam A. M. Capretz, Majid Fekri, Bala Gopalakrishnan:
(CF)2 architecture: contextual collaborative filtering. Inf. Retr. J. 21(6): 541-564 (2018) - [c14]Xiaoou Monica Zhang, Katarina Grolinger, Miriam A. M. Capretz, Luke Seewald:
Forecasting Residential Energy Consumption: Single Household Perspective. ICMLA 2018: 110-117 - 2017
- [j6]Alexandra L'Heureux, Katarina Grolinger, Hany F. ElYamany, Miriam A. M. Capretz:
Machine Learning With Big Data: Challenges and Approaches. IEEE Access 5: 7776-7797 (2017) - [c13]Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz:
A Gamification Framework for Sensor Data Analytics. ICIOT 2017: 74-81 - [c12]Norman L. Tasfi, Wilson A. Higashino, Katarina Grolinger, Miriam A. M. Capretz:
Deep Neural Networks with Confidence Sampling for Electrical Anomaly Detection. iThings/GreenCom/CPSCom/SmartData 2017: 1038-1045 - 2016
- [c11]Katarina Grolinger, Miriam A. M. Capretz, Luke Seewald:
Energy Consumption Prediction with Big Data: Balancing Prediction Accuracy and Computational Resources. BigData Congress 2016: 157-164 - [c10]Daniel B. Araya, Katarina Grolinger, Hany F. ElYamany, Miriam A. M. Capretz, Girma T. Bitsuamlak:
Collective contextual anomaly detection framework for smart buildings. IJCNN 2016: 511-518 - 2015
- [j5]Katarina Grolinger, Emna Mezghani, Miriam A. M. Capretz, Ernesto Exposito:
Collaborative knowledge as a service applied to the disaster management domain. Int. J. Cloud Comput. 4(1): 5-27 (2015) - [c9]Hany F. El Yamany, Marwa F. Mohamed, Katarina Grolinger, Miriam A. M. Capretz:
A Generalized Service Replication Process in Distributed Environments. CLOSER 2015: 186-193 - [c8]Sara S. Abdelkader, Katarina Grolinger, Miriam A. M. Capretz:
Predicting Energy Demand Peak Using M5 Model Trees. ICMLA 2015: 509-514 - [c7]Mauro Ribeiro, Katarina Grolinger, Miriam A. M. Capretz:
MLaaS: Machine Learning as a Service. ICMLA 2015: 896-902 - 2014
- [j4]Katarina Grolinger, Miriam A. M. Capretz, Americo Cunha, Saïd Tazi:
Integration of business process modeling and Web services: a survey. Serv. Oriented Comput. Appl. 8(2): 105-128 (2014) - [c6]Katarina Grolinger, Michael A. Hayes, Wilson A. Higashino, Alexandra L'Heureux, David S. Allison, Miriam A. M. Capretz:
Challenges for MapReduce in Big Data. SERVICES 2014: 182-189 - 2013
- [j3]Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam A. M. Capretz:
Data management in cloud environments: NoSQL and NewSQL data stores. J. Cloud Comput. 2: 22 (2013) - [c5]Katarina Grolinger, Miriam A. M. Capretz, Emna Mezghani, Ernesto Exposito:
Knowledge as a Service Framework for Disaster Data Management. WETICE 2013: 313-318 - 2012
- [c4]Katarina Grolinger, Miriam A. M. Capretz, José R. Martí, Krishan D. Srivastava:
Ontology-based Representation of Simulation Models. SEKE 2012: 432-437 - 2011
- [j2]Katarina Grolinger, Miriam A. M. Capretz:
A unit test approach for database schema evolution. Inf. Softw. Technol. 53(2): 159-170 (2011) - [c3]Kevin P. Brown, Katarina Grolinger, Miriam A. M. Capretz:
Data Providing Web Service-based integration framework for use in a health care context. CCECE 2011: 1069-1072 - [c2]Katarina Grolinger, Miriam A. M. Capretz, Adam Shypanski, Gagandeep S. Gill:
Federated critical infrastructure simulators: Towards ontologies for support of collaboration. CCECE 2011: 1503-1506 - [c1]Katarina Grolinger, Kevin P. Brown, Miriam A. M. Capretz:
From Glossaries to Ontologies: Disaster Management Domain(S). SEKE 2011: 402-407
1990 – 1999
- 1999
- [j1]Bojan Jerbc, Katarina Grolinger, Bozo Vranjs:
Autonomous agent based on reinforcement learning and adaptive shadowed network. Artif. Intell. Eng. 13(2): 141-157 (1999)
Coauthor Index
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last updated on 2023-03-22 22:31 CET by the dblp team
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