DBIA Lab:
Databases and Artificial Intelligence Laboratory
The Database and Artificial Intelligence (DBIA) laboratory is a center of excellence for Artificial Intelligence and Databases research since its founding in 1997. Our current research interests reside in machine learning, neural networks, computer vision, data mining and databases.
The obtained results of the member of the laboratory were published in prestigious international journals and conferences. We believe that the results of our research will influence the way artificial intelligence and databases will be used to build future intelligent products inside modern enterprise.
Research Areas
Research Fields:Artificial intelligence
Computer graphics and machine vision
Database systems
Big data analysis and management
Computer vision
Data mining
Data modeling
Data visualization
Distributed database systems
Expert and decision systems
Fuzzy logic
Game engineering
Graphics rendering and animation
Image and video processing
Knowledge-based systems
Machine learning
Modeling and simulation systems
Neural networks
Pattern recognition
Visual databases
Current Members
Director:
Research Team:
Selected Research Projects
Supervised PhD Theses
- Marius BABA: Behavior classification using video sensor networks in urban environments , Supervisor: Ionel JIAN, 2021
- Adriana Marina MERCIONI: Improving performance of deep neural networks by developing novel activation functions, Supervisor: Ștefan HOLBAN, 2021
- Nicolae Teodor MELIȚĂ: Contributions to data analysis and processing in genetic analysis, Supervisor: Ștefan HOLBAN, 2016
- Doru TODINCA: Resource allocation techniques for improving the performance of data transfer over GPRS/EGPRS networks, Supervisor: Ștefan HOLBAN, 2005
- Dan PESCARU: Bridging the Gap between Object Oriented Modeling and Implementation Languages Using a Meta-Language Approach, Supervisor: Ionel JIAN, 2004
Affiliated Rooms
- B623
Description, History and Other Info
Research center vision
- Human resources
- Industry-Academia partnership
- Research projects
Research projects
- Structural funds
- Bilateral projects
- International research projects (FP7, CHIST-ERA)
- National research projects
Industry partners
- Everseen
- Continental Automotive
- Visma
- Piconet
- Krohne
Academic partners
- University of Manchester (Marea Britanie)
- University of Innsbruck (Austria)
- University of New York at Stony Brook (USA)
- Université Nice Sophia Antipolis (France)
- Dublin City University (Ireland)
Papers
- Petre Birtea, Dan Comănescu, Călin-Adrian Popa, Averaging on Manifolds by Embedding Algorithm. Journal of Mathematical Imaging and Vision, Vol. 49, Nr. 2, pag. 454-466, 2014. (ISI Impact Factor 1.603, Q1)
- Călin-Adrian Popa, Eva Kaslik, Multistability and multiperiodicity in impulsive hybrid quaternion-valued neural networks with mixed delays. Neural Networks, Vol. 99, pag. 1-18, 2018. (ISI Impact Factor 5.785, Q1)
- Călin-Adrian Popa, Global exponential stability of octonion-valued neural networks with leakage delay and mixed delays. Neural Networks, Vol. 105, pag. 277-293, 2018. (ISI Impact Factor 5.785,Q1)
- Călin-Adrian Popa, Global exponential stability of neutral-type octonion-valued neural networks with time-varying delays. Neurocomputing, Vol. 309, pag. 117-133, 2018. (ISI Impact Factor 4.072,Q1)
- Călin-Adrian Popa, Global μ-stability of neutral-type impulsive complex-valued BAM neural networks with leakage delay and unbounded time-varying delays. Neurocomputing, 2019. (ISI Impact Factor 4.072, Q1)
- M. Baba, V. Gui, C. Cernazanu, D. Pescaru, "A Sensor Network Approach for Violence Detection in Smart Cities Using Deep Learning", Sensors, Vol. 19(7), MDPI Basel, April 2019, pp. 1-17. (ISI Q1)
- D. Pescaru, D.I. Curiac, "Ensemble based traffic light control for city zones using a reduced number of sensors", Transportation Research Part C: Emerging Technologies, Elsevier, Vol. 46, September 2014, Pages 261-273 (ISI Q1)
- D. Pescaru, D.I. Curiac, "Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion", Sensors, Vol. 14(3), MDPI Basel, March 2014, pp. 4211-4224. (ISI Q1)
- V. Subramanian, M. Gilberti, A. Doboli, D. Pescaru, "A Goal-Oriented Programming Framework for Grid Sensor Networks with Reconfigurable Embedded Nodes", ACM Transactions on Embedded Computing Systems (TECS), Vol. 11 Iss. 4, ACM New York, December 2012, pp. 79:1-79:30. (ISI-IF = 1.368)
- C. Istin, D. Pescaru, A. Doboli, "Stochastic Model-based Heuristics for Fast Field of View Loss Recovery in Urban Traffic Management Through Networks of Video Cameras", IEEE Transactions on Intelligent Transportation Systems, Vol. 12 Iss. 3, IEEE Press, September 2011, pp. 895-907. (ISI Q1)
Former Members
Contact
DBIA Lab: Databases and Artificial Intelligence Laboratory
Department of Computer and Information Technology
Politehnica University of Timisoara
2, Vasile Pârvan Bvd., 300223, Timisoara, Romania
Room B623
(0256 40) 3277