• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer

Centre for Artificial Intelligence and Cybersecurity – AIRI

  • Home
  • About Us
    • Vision, Mission and Goals
    • Center Activities
    • Center Faculty
    • Steering Committee
    • Press
  • Research
    • Scientific Projects
    • Research Papers
  • Laboratories
    • Machine Learning
    • Natural Speech & Language Processing
    • Blockchain Technology
    • Information Processing & Pattern Recognition
    • AI in Medicine
    • Data Mining
    • Computer Vision
    • Human-Computer Interaction
    • Maritime Cybersecurity
    • Autonomous Navigation
    • AI in Mechatronics
    • AI in Education
    • Hybrid Computational Methods
    • Drug Design
    • Legal Aspects of AI
    • Ethically Aligned AI
    • Cultural Complexity
  • Collaboration
    • Industry Collaboration
    • Industry Projects
    • International Collaboration
  • News
  • Contact

Ivan Štajduhar, D.Sc.

University of Rijeka, Faculty of Engineering

Ivan Štajduhar, D.Sc., is a researcher in machine learning. His research focus is directed primarily towards the development of machine-learning-based solutions for medical diagnostics. He participated in several research projects, funded by local, national and European funding sources, and has co-authored a number of papers in peer-reviewed journals. He is holding the position of associate professor at the University of Rijeka Faculty of Engineering (RITEH), and is presently vice dean for business affairs at RITEH, as well as deputy head of the UNIRI Center for Artificial Intelligence and Cybersecurity (AIRI). He is a full-time employee at RITEH.

Author's Projects

Machine Learning for Knowledge Transfer in Medical Radiology

Machine Learning for Knowledge Transfer in Medical Radiology

European Network for assuring food integrity using non-destructive spectral sensors

National Competence Centres in the Framework of EuroHPC (EUROCC)

Hyperspectral Image Analysis Using Machine Learning and Adaptive Data-Driven Filtering

Development of machine-learning-based techniques for illness and injury detection in medical images

Computer-Aided Digital Analysis And Classification of Signals

Computer-Aided Digital Analysis And Classification of Signals

A Network for Gravitational Waves, Geophysics and Machine Learning

Image Processing, Information Engineering & Interdisciplinary Knowledge Exchange

Author's Research Papers

Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification

Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network

Automatic Annotation of Narrative Radiology Reports

Adaptive Filtering and Analysis of EEG Signals in the Time-Frequency Domain Based on the Local Entropy

Automatic Music Transcription for Traditional Woodwind Instruments Sopele

Automatic Music Transcription for Traditional Woodwind Instruments Sopele

Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection

Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection

Adaptive State Estimator With Intersection of Confidence Intervals Based Preprocessing

Mirroring Quasi-Symmetric Organ Observations for Reducing Problem Complexity

Semi-automated detection of anterior cruciate ligament injury from MRI

Uncensoring censored data for machine learning: A likelihood-based approach

Learning Bayesian networks from survival data using weighting censored instances

Impact of censoring on learning Bayesian networks in survival modelling

Primary Sidebar

Latest Projects

Machine Learning for Knowledge Transfer in Medical Radiology

Estimating River Discharges in Highly Stratified Estuaries

Multilayer Framework for the Information Spreading Characterization in Social Media during the COVID-19 Crisis (InfoCoV)

European Network for assuring food integrity using non-destructive spectral sensors

National Competence Centres in the Framework of EuroHPC (EUROCC)

Latest Research Papers

Rule-Based EEG Classifier Utilizing Local Entropy of Time–Frequency Distributions

Rethinking Effects of Innovation in Competition In The Era of New Digital Technologies

A Comparison of Approaches for Measuring the Semantic Similarity of Short Texts Based on Word Embeddings

Indoor Localization Based on Infrared Angle of Arrival Sensor Network

Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of Intersection of Confidence Intervals Rule

Latest News

U Rijeci radi Centar za umjetnu inteligenciju, već su u prvoj godini rada povukli šest milijuna u 14 projekata

UNIRI Excellence Awards in Science

Talk on conference “Exploring Digital Legal Landscapes”

ICAIH 2020 conference presentation

International conference “Exploring Digital Legal Landscapes” – 11th of December, 2020

We provide the expertise for solving real world problems using AI

If your company wants to implement artificial intelligence in your products or services, or increase your level of cybersecurity, our multidisciplinary team of scientists is your ideal partner.

Contact us

Footer

Center for Artificial Intelligence and Cybersecurity
  • jlerga@airi.uniri.hr
  • +385 51 406 500

University of Rijeka

University of Rijeka

About the Center

  • About Us
  • News
  • Privacy Policy
  • Contact

Center Activities

  • Laboratories
  • Scientific Projects
  • Industry Projects
  • Research Papers
  • Industry Collaboration
  • International Collaboration

Footer bottom left

© 2020 Center for Artificial Intelligence and Cybersecurity, all rights reserved.

Designed & developed by Nela Dunato Art & Design