Drago Torkar

Research areas
  • Computer vision
  • Pattern recognition
  • Image processing
  • Machine vision

  • Projects
  • Distributed Artificial Intelligent Systems (2021-2024)
  • Computer structures and systems (2019-2024)
  • Intelligent Secure Trustable Things (2020-2023)
  • Supporting Active Ageing through Multimodal coaching (2017-2021)
  • Advanced recognition (2020)
  • Machine vision quality control of molded plastic parts (2019-2020)
  • Resource Efficient Food and dRink for the Entire Supply cHain (2015-2019)
  • iNet - The Impact of Net Height in Table Tennis (2017-2018)
  • Computer structures and systems (2015-2018)
  • Computer structures and systems (2009-2014)
  • Mobile application for food ingredients informing (2009-2010)
  • Development and implementation of a new PIM binder system using advanced methods (2008-2010)
  • The role of Luka Koper in logistic support of the Slovenian Armed Forces and allies (2006-2008)
  • Adaptive Robots for Flexible Manufacturing Systems (2005-2008)
  • Computing structures and systems (2004-2008)
  • Upgrade of light armoured wheeled vehicles VALUK 6x6 (2006-2007)
  • Vision interface for ABB robots (2006)
  • Secure data storage unit based on new ferroelectric semiconductor memory devices (2004-2006)
  • 2D and 3D digital map system for land, aerial and sea orientation (2004-2005)
  • Modeling rheological properties of ceramic-paraffine suspensions for low-pressure injection-moulding (2003-2004)

  •  
    Modeling rheological properties of ceramic-paraffine suspensions for low-pressure injection-moulding[X]
    • contractor: AET, Tolmin, Slovenia
    • duration: 2003-2004
    • content:
      With the proposed project we intend to solve the complex problem of modelling the rheological properties of ceramic-paraffin suspensions with regard to their composition, a key parameter in low-pressure injection moulding in the production of ceramic parts at AET Tolmin.
      In the first stage we will simulate the moulding process and establish the influence of process parameters on the flowability. In particular, we will pay special attention to the dynamic viscosity. For a specific mould we will study both the shear-rate distribution in the mould and its dynamic range. The results will be verified using real systems from production.
      In the next stage, based on viscosity measurements in the determined shear-rate range, we will construct a model of the visco-elastic behaviour. The model parameters will be predicted by using a constructed artificial neural network (ANN) that is trained with experimental data. We will test various topologies and learning algorithms and the best performing one will be selected. The model and the ANN's behaviour will be thoroughly tested with new experimental data.
      Finally, another ANN will be constructed to model the relationship between the ceramic composition and the desired rheological properties. This represents a complicated inverse multi-value problem; therefore, we will take special care with the design of the learning algorithm. The test set will comprise data from an experimental database and from artificially generated examples using the ANN from the previous stage.
      The result will be a methodological approach to the preparation of ceramic suspensions for low-pressure injection moulding. This will enable us to select the appropriate suspension composition for a specific mould.

  • Computing structures and systems (1999-2003)
  • High performance evolutionary techniques in hardware-software codesign (1999-2001)
  • PEMCAS: personal monitor for capability supervision (1997-1998)
  • Architectural synthesis of computer systems with testability issues (1995-1998)
  • Publications
    Journal articles
  • Biomarkers of pre-existing risk of torsade de pointes under Sotalol treatment, J. ELECTROCARDIOL. (2020)
  • Dynamic features of cardiac vector as alternative markers of drug-induced spatial dispersion, J PHARMACOL TOX MET (2020)
  • Knee stiffness and viscosity of human cadaver - Wartenberg test, BJBMS (2017)
  • Cell counting tool parameters optimization approach for electroporation efficiency determination of attached cells in phase contrast images, J.Microsc. (2011)
  • Identification of radon anomalies in soil gas using decision trees and neural networks, Nukleonika (2010)
  • Application of artificial neural networks in simulating radon levels in soil gas, ChemGe (2010)
  • Visual control of an industrial robot manipulator: Accuracy Estimation, Stroj. vestn. (2009)
  • Robot Vision Accuracy Estimation, Elektroteh. vest. (2009)
  • Apparent viscosity prediction of alumina-paraffin suspensions using artificial neural networks, J. mater. process. technol. (2008)
  • Evaluation of accuracy in a 3D reconstruction system, WSEAS Trans. Syst. Control (2007)
  • Control of a robotic manipulator by visual and speech information, Eng. rev. (2002)
  • An uncalibrated robot system for reaching and grasping objects in unpredictable physical environment, J. Electr. Eng. (2001)
  • GPS positioning and digital map processing in 2D and 3D terrain environment, J. Comput. Inf. Technol. (1994)
  • Computer processing of hard-copy maps and their application in satelite positioning, J. Commun. (1994)
  • Reflection on light distribution measurement, Sens. Rev. (1992)
  • Conference papers
  • Food Waste Ontology: A Formal Description of Knowledge from the Domain of Food Waste, BFNDMA 2019 at IEEE BigData 2019
  • Analysis of an Electrocardiographic Multilead System using Artificial Neural Networks - A Study of the Dispersion during Premature Ventricular Stimulation, Biosignals 2016
  • Accuracy of a 3D reconstruction system, ISPRA 2007
  • Robot TCP positioning with vision : accuracy estimation of a robot visual control system, ICINCO 2007
  • Estimation of accuracy for robot vision control, SHR2007
  • Radon in soil gas : application of neuron networks to identify anomalies caused by earthquakes, Hazards 2006
  • Dynamic viscosity prediction of alumina-paraffin suspensions using artificial neural networks, AERC 2005
  • The use of numerical simulation for the study of low-pressure injection moulding of alumina-paraffin suspensions, AERC 2003
  • Books & Chapters in Books
  • Optimal lead selection for evaluation ventricular premature beats using machine learning approach, (2017)
  • Radon as Earthquake Precursor - Methods for Detecting Anomalies, InTech - Open Access Publisher (2011)