K
Krishna Dubba
Researcher at University of Leeds
Publications - 10
Citations - 179
Krishna Dubba is an academic researcher from University of Leeds. The author has contributed to research in topics: Process automation system & Inductive logic programming. The author has an hindex of 5, co-authored 10 publications receiving 169 citations.
Papers
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Journal ArticleDOI
Learning relational event models from video
TL;DR: A novel framework (Relational Event Model INDuction) for supervised relational learning of event models from large video datasets using ILP is presented and an extension to the framework is presented by integrating an abduction step that improves the learning performance when there is noise in the input data.
Proceedings ArticleDOI
Event Model Learning from Complex Videos using ILP
TL;DR: A novel supervised learning framework to learn event models from large video datasets (~2.5 million frames) using ILP is presented and efficiency is achieved via the learning from interpretations setting and using a typing system.
Journal ArticleDOI
The RACE Project : Robustness by Autonomous Competence Enhancement
Joachim Hertzberg,Jianwei Zhang,Liwei Zhang,Sebastian Rockel,Bernd Neumann,Jos Lehmann,Krishna Dubba,Anthony G. Cohn,Alessandro Saffiotti,Federico Pecora,Masoumeh Mansouri,Štefan Konečný,Martin Günther,Sebastian Stock,Luís Seabra Lopes,Miguel Oliveira,Gi Hyun Lim,Hamidreza Kasaei,Vahid Mokhtari,Lothar Hotz,Wilfried Bohlken +20 more
TL;DR: The general system architecture is introduced and some results in detail regarding hybrid reasoning and planning used in RACE are sketches, and instances of learning from the experiences of real robot task execution are sketched.
Book ChapterDOI
Interleaved inductive-abductive reasoning for learning complex event models
TL;DR: The proposed model provides a blue-print for interfacing common-sense reasoning about space, events and dynamic spatio-temporal phenomena with quantitative techniques in activity recognition as well as improving the inductive learning to get semantically meaningful event models.
Proceedings Article
Grounding Language in Perception for Scene Conceptualization in Autonomous Robots
Krishna Dubba,M.R. De Oliveira,Gi Hyun Lim,H. Kasaei,Luís Seabra Lopes,Ana Maria Tomé,Anthony G. Cohn +6 more
TL;DR: A cognitive architecture and learning framework for robot learning through natural human supervision and using multiple input sources by grounding language in perception is presented.