Laboratorij za programsko inženjerstvo i obradu informacija

English

Istraživači

Projekti

  • 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 (2020-2021).

  • “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).

Radovi u časopisima

  • 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

Nastavna oprema

meta2.jpg

Meta 2 AR development Kit
 

dobot.jpg

Dobot Magician Educational + extras

DiddyBorg.jpg

DiddyBorg

Bonaca.jpg

Bonaca GPU workstation

   

 

SEIPlab stare stranice

Voditelj izv. prof. dr. sc. Ivan Štajduhar person.image.file.alt
Telefon
+385 51 651448, int. 2448 (Ured)
Lokacija
1-49b