Researchers

• Prof. Ivan Štajduhar

• Assist. Prof. Goran Mauša

• Assoc. Prof. Jonatan Lerga

• Franko Hržić, PhD student

• Teo Manojlović, PhD student

• Arian Skoki, PhD student

• Mateja Napravnik, PhD student

• Robert Baždarić, postdoctoral researcher

Projects

• "Machine Learning for Knowledge Transfer in Medical Radiology", Croatian Science Foundation research project IP-2020-02-3770 (2021-2024).

• "European Network for assuring food integrity using non-destructive spectral sensors", COST Action CA19145 (2020-2024).

• "Hyperspectral Image Analysis Using Machine Learning and Adaptive Data-Driven Filtering", bilateral project in cooperation with the Medical Physics Group at the Faculty of Mathematics and Physics, Ljubljana, Slovenia (2020-2022).

• “Development of machine-learning-based techniques for illness and injury detection in medical images”, University of Rijeka grant uniri-tehnic-18-15 (2019-2022).

• “Computer-aided digital analysis and classification of signals”, University of Rijeka grant uniri-tehnic-18-17 (2019-2022).

• "A network for gravitational waves, geophysics and machine learning", COST Action CA17137 (2018-2022).

• "Adapting multi-objective genetic programming for solving complex combinatorial problems", University of Rijeka grant 18.10.2.1.01 (2018-2019).

• "An empirical comparison of machine learning based approaches for code smell detection", bilateral project in cooperation with the Information Systems Laboratory (M. Heričko), Maribor, Slovenia (2018-2019).

• “Thorax motion supervision in radiotherapy using machine learning techniques”, bilateral project in cooperation with the Medical Physics Group at the Faculty of Mathematics and Physics, Ljubljana, Slovenia (2018-2019).

• "RadiologyNet: Machine Learning for Knowledge Transfer”, University of Rijeka grant 16.09.2.2.05 (2017).

• “Implementation of Time-Frequency and other Advanced Algorithms to Biomedical Signal Analysis”, University of Rijeka grant 16.09.2.2.04 (2017).

• "Automatic Detection of Knee Ligament Injury from Magnetic Resonance Scans”, The Scientific & Technological Research Council of Turkey (TUBITAK), in collaboration with the Computer Vision and Pattern Analysis Laboratory (VPALAB), Sabanci University, Istanbul, Turkey (2015).

• “Analysis and innovative approaches to developing, managing and applying complex software systems”, University of Rijeka grant 13.09.2.2.16 (2014-2018).

• “Evolving Software Systems: Analysis and Innovative Approaches for Smart Management”, CSF research project 7945 (2015-2018).

Journal papers

• M. Njirjak, E. Otović, D. Jozinović, J. Lerga, G. Mauša, A. Michelini, I. Štajduhar. The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data. Volume 10 (6), 965, 2022.
  Mathematics: WoS JCR Q1, Scimago Q2, impact factor 2.258

• E. Otović, M. Njirjak, D. Jozinović, G. Mauša, A. Michelini, I. Štajduhar. Intra-domain and cross-domain transfer learning for time series data – How transferable are the features?, Vol. 239, 107976, 2022.
  Knowledge-Based Systems: WoS JCR Q1, Scimago Q1, impact factor 8.038

• D. Jozinović, A. Lomax, I. Štajduhar, A. Michelini. Transfer learning: Improving neural network based prediction of earthquake ground shaking for an area with insufficient training data, Vol. 229, Issue 1, Pages 704-718.
  Geophysical Journal International: WoS JCR Q2, Scimago Q1, impact factor 2.934

• F. Hržić, M. Janisch, I. Štajduhar, J. Lerga, E. Sorantin, S. Tschauner. Modeling Uncertainty in Fracture Age Estimation from Pediatric Wrist Radiographs, Vol. 9, Issue 24, 3227, 2021.
  Mathematics: WoS JCR Q1, Scimago Q2, impact factor 2.258

• F. Hržić, I. Žužić, S. Tschauner, I. Štajduhar. Cast suppression in radiographs by generative adversarial networks, Vol 28, Issue 12, pp. 2687-2694, 2021.
  Journal of the American Medical Informatics Association: WoS JCR Q1, Scimago Q1, impact factor 4.497

• T. Manojlović, I. Štajduhar. Deep Semi-Supervised Algorithm for Learning Cluster-Oriented Representations of Medical Images Using Partially Observable DICOM Tags and Images, Vol. 11, Issue 10, 1920, 2021.
  Diagnostics: WoS JCR Q2, Scimago Q3, impact factor 3.706

• F. Nikolić, I. Štajduhar, M. Čanađija. Casting Microstructure Inspection Using Computer Vision: Dendrite Spacing in Aluminum Alloys, Volume 11, Issue 5, 756, 2021.
  Metals: WoS JCR Q2, Scimago Q1, impact factor 2.351

• S. Ljubic, F. Hržić, A. Salkanovic, I. Štajduhar. Augmenting Around-Device Interaction by Geomagnetic Field Built-in Sensor Utilization, Vol. 21, Issue 9, 3087, 2021.
  Sensors: WoS JCR Q1, Scimago Q2, impact factor 3.275

• F. Hržić, S. Tschauner, E. Sorantin, I. Štajduhar. XAOM: A method for automatic alignment and orientation of radiographs for computer-aided medical diagnosis, Vol. 132, pp. 104300:1-12, 2021.
  Computers in biology and medicine: WoS JCR Q1, Scimago Q2, impact factor 3.434

• B. Petrovska, E. Zdravevski, P. Lameski, R. Corizzo, I. Štajduhar, J. Lerga. Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification, Vol. 20, Issue 14, 3906, 2020.
  Sensors: WoS JCR Q1, Scimago Q2, impact factor 3.275

• D. Jozinović, A. Lomax, I. Štajduhar, A. Michelini. Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network, Vol. 222, Issue 2, Pages 1379-1389, 2020.
  Geophysical journal international: WoS JCR Q2, Scimago Q1, impact factor 2.777

• I. Krsnik, G. Glavaš, M. Krsnik, D. Miletić, I. Štajduhar. Automatic Annotation of Narrative Radiology Reports, Vol. 10 (4), 196, 2020.
  Diagnostics: WoS JCR Q1, Scimago Q2, impact factor 3.110

• G.M. Jadav, J.  Lerga, I. Štajduhar. Adaptive filtering and analysis of EEG signals in the time-frequency domain based on the local entropy, Vol. 2020, Issue 1, Pages 1-18, 2020.
  EURASIP Journal on Advances in Signal Processing: WoS JCR Q3, Scimago Q2, impact factor 1.749

• A. Skoki, S. Ljubić, J. Lerga, I. Štajduhar. Automatic Music Transcription for Traditional Woodwind Instruments Sopele, Volume 128, Pages 340-347, 2019.
  Pattern Recognition Letters:WoS JCR Q2, Scimago Q1, impact factor 2.810

• D. Kalafatovic, G. Mauša, T. Todorovski, E. Giralt. Algorithm-supported, mass and sequence diversity-oriented random peptide library design, Vol. 11, 11:25, pp. 1 – 15, 2019.
  Journal of Cheminformatics: Q1 (JCR), Q1 (WoS), impact factor 3.893

• Hržić, F.; Štajduhar, I.; Tschauner, S.; Sorantin, E., Lerga, J.: Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection, vol. 21, no. 4, pp. 338:1-18, 2019.
  Entropy: Q2 (JCR), Q2 (WoS), impact factor 2.305

• Kirinčić, V.; Čeperić, E.; Vlahinić, S.; Lerga, J.: Support Vector Machine State Estimation, Applied Artificial Intelligence, vol. , no. , pp. , 2019.
  Applied Artificial Intelligence: Q3 (JCR), Q4 (WoS), impact factor 0.587

• Lerga, J.; Mandić, I.; Peić, H.; Brščić, D.: An adaptive method based on the improved LPA-ICI algorithm for MRI enhancement, The Imaging Science Journal, vol. 66, no. 6, pp. 372-381, 2018.
  The Imaging Science Journal: Q2 (JCR), Q4 (WoS), impact factor 0.366

• Mandić, I.; Peić, H.; Lerga, J.; Štajduhar, I.: Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm, Journal of Imaging, vol. 4, no. 2, pps. 15, 2018.
  Journal of Imaging: WoS CC

• Lerga, J.; Kirinčić, V.; Franković, D.; Štajduhar, I.: Adaptive State Estimator With Intersection of Confidence Intervals Based Preprocessing, International Journal of Electrical Power & Energy Systems, vol. 102, pp. 413-420, 2018.
  International Journal of Electrical Power & Energy Systems: Q1 (JCR), Q1 (WoS), impact factor 3.610

• Lerga, J.; Grbac, E.; Sucic, V.; Saulig, N.: Adaptive Methods for Video Denoising Based on the ICI, FICI, and RICI Algorithms, Tehnički vjesnik, vol. 25, no. suppl. 1, pp. 1-6, 2018. 
  Tehnički vjesnik: Q2 (JCR), Q4 (WoS), impact factor 0.686

• G. Mauša, T. Galinac Grbac. Co-evolutionary Multi-Population Genetic Programming for Classification in Software Defect Prediction: an Empirical Case Study, Vol. 55, pp. 331 – 351, 2017.
  Applied soft computing: Q1 (JCR), Q1 (WoS), impact factor 3.907

• Štajduhar, I.; Tomić, M.; Lerga, J.: Mirroring quasi-symmetric organ observations for reducing problem complexity, Expert Systems with Applications, vol. 85, pp. 318–334, 2017.
  Expert Systems with Applications: Q1 (JCR), Q1 (WoS), impact factor 3.768

• Volaric, I.; Lerga, J.; Sucic, V.: A Fast Signal Denoising Algorithm Based on the LPA-ICI Method for Real-Time Applications, Circuits, Systems, and Signal Processing, vol. 36, pp. 4653-4669, 2017.
  Circuits, Systems, and Signal Processing: Q2 (JCR), Q2 (WoS), impact factor 1.998

• Lerga, J.; Saulig, N.; Mozetič, V.: Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis, Computers In Biology And Medicine, vol. 80, pp. 1-13, 2017.
  Computers In Biology And Medicine: Q2 (JCR), Q2 (WoS), impact factor 2.115

• I. Štajduhar, M. Mamula, D. Miletić, G. Unal, Semi-automated detection of anterior cruciate ligament injury from MRI, Volume 140, Pages 151–164, 2017.
  Computer Methods and Programs in Biomedicine: Q1 (JCR), Q1 (WoS), impact factor 2.674

• Šegon, G.; Lerga, J.; Sucic, V.: Improved LPA-ICI-Based Estimators Embedded in a Signal Denoising Virtual Instrument, Signal, Image and Video Processing, vol. 11, no. 2, pp. 211-217, 2017.
  Signal, Image and Video Processing: Q2 (JCR), Q3 (WoS), impact factor 1.643

• G. Mauša, T. Galinac Grbac, B. Dalbelo Bašić. A Systematic Data Collection Procedure for Software Defect Prediction, Vol. 13 (1), 2016, pp. 173–197, 2016.
  Computer Science and Information Systems Journal

• Bujak M; Ratkaj I.; Markova-Car E.; Jurisic D.; Horvatic A.; Vucinic S.; Lerga J.; Baus Loncar M.; Pavelic K.; Kraljevic Pavelic S.: Inflammatory Gene Expression Upon TGF-b1-Induced p38 Activationin Primary Dupuytren’s Disease Fibroblasts, Frontiers in Molecular Biosciences, vol. 2; pp. 1-9, 2015.

• Lerga, J.; Grbac E.; Sucic, V.: An ICI Based Algorithm for Fast Denoising of Video Signals, Automatika, vol. 55, no. 3, pp. 351-358, 2014. 
  Automatika: Q3 (JCR), Q4 (WoS), impact factor 0.307

• Sucic, V.; Lerga, J.; Boashash, B.: Multicomponent Noisy Signal Adaptive Instantaneous Frequency Estimation Using Components Time Support Information, IET Signal Processing, vol. 8, no. 3, pp. 277-284, 2014.
  IET Signal Processing: Q2 (JCR), Q3 (WoS), impact factor 1.495

• Lerga, J.; Franusic, M.; Sucic, V.: Parameters Analysis for the Time-Varying Automatically Adjusted LPA Based Estimators, Journal of Automation and Control Engineering, vol. 2, no. 3; pp. 203-208, 2014.

• Sucic, V.; Lerga, J.; Vrankic, M.: Adaptive Filter Support Selection for Signal Denoising Based on the Improved ICI Rule, Digital Signal Processing, vol. 23, no. 1, pp. 65-74, 2013. 
  Digital Signal Processing: Q1 (JCR), Q2 (WoS), impact factor 1.495

• I. Štajduhar, B. Dalbelo Bašić, Uncensoring censored data for machine learning: A likelihood-based approach, Volume 39, Issue 8, 2012, Pages 7226-7234
  Expert Systems with Applications: Q1 (JCR), Q1 (WoS), impact factor 3.768

• Lerga, J.; Sucic, V.; Grbac, E.: An Adaptive Method for Video Denoising Based on the ICI Rule, Engineering Review, vol. 32, no. 1; pp. 33-40, 2012.

• Lerga, J.; Sucic, V.; Vrankić, M.: Separable Image Denoising Based on the Relative Intersection of Confidence Intervals Rule, Informatica, vol. 22, no. 3, pp. 383-394, 2011.
  Informatica: Q2 (JCR), Q1 (WoS), impact factor 1.627

• Lerga J.; Sucic, V.; Boashash, B.: An Efficient Algorithm for Instantaneous Frequency Estimation of Nonstationary Multicomponent Signals in Low SNR, EURASIP Journal on Advances in Signal Processing, vol. 2011, pp. 1-16, 2011. 
  EURASIP Journal on Advances in Signal Processing: Q2 (JCR), Q3 (WoS), impact factor 0.811

• I. Štajduhar, B. Dalbelo Bašić, Learning Bayesian networks from survival data using weighting censored instances, Volume 43, Issue 4, 2010, Pages 613-622
  Journal of Biomedical Informatics: Q1 (JCR), Q1 (WoS), 2.882

• Lerga, J.; Sucic, V.: Nonlinear IF Estimation Based on the Pseudo WVD Adapted Using the Improved Sliding Pairwise ICI Rule, IEEE Signal Processing Letters, vol. 16, no. 11, pp. 953-956, 2009.
  IEEE Signal Processing Letters: Q1 (JCR), Q2 (WoS), impact factor 1.173

• I. Štajduhar, B. Dalbelo Bašić, N. Bogunović, Impact of censoring on learning Bayesian networks in survival modelling, Volume 47, Issue 3, 2009, Pages 199-217
  Artificial Intelligence in Medicine: Q1 (JCR), Q1 (WoS), impact factor 2.879

• Lerga, J.; Vrankic, M.; Sucic, V.: A Signal Denoising Method Based on the Improved ICI Rule, IEEE Signal Processing Letters, vol. 15, pp. 601-604, 2008.
  IEEE Signal Processing Letters: Q1 (JCR), Q2 (WoS), impact factor 1.203

Teaching equipment

Research equipment

SEIPlab old webpage (link)