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

Center for Artificial Intelligence and Cybersecurity – AIRI

  • Home
  • About Us
    • Center Activities
    • Vision, Mission and Goals
    • 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
    • Complex Networks
    • 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
    • Trustworthy and Explainable AI
  • Collaboration
    • Industry Collaboration
    • Industry Projects
    • International Collaboration
  • News
  • Contact
  • Login

Machine Learning Laboratory

XAOM: A method for automatic alignment and orientation of radiographs for computer-aided medical diagnosis

16.03.2021

Background and objectives: Computer-aided diagnosis relies on machine learning algorithms that require filtered and preprocessed data as the input. Aligning the image in the desired direction is an additional manual step in post- processing, commonly overlooked due to workload issues. Several state-of-the-art approaches for fracture detection and disease-struck region segmentation benefit from correctly oriented images, […]

Machine Learning for Knowledge Transfer in Medical Radiology

26.12.2020

Machine Learning for Knowledge Transfer in Medical Radiology

Medical radiology is often used in clinical analysis to establish a medical diagnosis in a non-invasive manner. By considering the morphological properties of the observed area, clinicians can determine the presence of an injury or a disease without the need for invasive surgery. The purpose of computer-aided diagnosis (CAD) is to help physicians with interpreting […]

ICAIH 2020 conference presentation

08.12.2020

Ivan Štajduhar gave a talk titled “The reach and limitations of machine intelligence” at the Third International Conference on Artificial Intelligence Humanities (ICAIH 2020), co-organised by the Chung-Ang University, Seoul, South Korea and the University of Rijeka.

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

14.07.2020

Scene classification relying on images is essential in many systems and applications related to remote sensing. The scientific interest in scene classification from remotely collected images is increasing, and many datasets and algorithms are being developed. The introduction of convolutional neural networks (CNN) and other deep learning techniques contributed to vast improvements in the accuracy […]

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

17.06.2020

There is an increasing need for the food industry to provide information on their products in order to satisfy quality standards and to protect their products from food fraud. Recent developments in technology, and advances in big data analytics, provide the opportunity for step-changes that can transform the role of food integrity assurance from one […]

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

17.06.2020

This study describes a deep convolutional neural network (CNN) based technique to predict intensity measurements (IMs) of earthquake ground shaking. The input data to the CNN model consists of multistation, 3C acceleration waveforms recorded during the 2016 Central Italy earthquake sequence for M ≥ 3.0 events. Using a 10 s window starting at the earthquake origin time, we find […]

National Competence Centres in the Framework of EuroHPC (EUROCC)

26.04.2020

H2020-JTI-EuroHPC-2019-2

Automatic Annotation of Narrative Radiology Reports

01.04.2020

Narrative texts in electronic health records can be efficiently utilized for building decision support systems in the clinic, only if they are correctly interpreted automatically in accordance with a specified standard. This paper tackles the problem of developing an automated method of labeling free-form radiology reports, as a precursor for building query-capable report databases in […]

Paper presented at ICPRAM 2020

26.02.2020

Teo Manojlović presented a paper titled “Using DICOM Tags for Clustering Medical Radiology Images into Visually Similar Groups”, at the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), Valletta, Malta, February 22-24, 2020. http://dx.doi.org/10.5220/0008973405100517

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

26.02.2020

The brain dynamics in the electroencephalogram (EEG) data are often challenging to interpret, specially when the signal is a combination of desired brain dynamics and noise. Thus, in an EEG signal, anything other than the desired electrical activity, which is produced due to coordinated electrochemical process, can be considered as unwanted or noise. To make […]

  • « Go to Previous Page
  • Go to page 1
  • Go to page 2
  • Go to page 3
  • Go to page 4
  • Go to Next Page »

Primary Sidebar

Latest Projects

Advanced Data Analysis Using Digital Signal Processing and Machine Learning Techniques

Compound Flooding in Coastal Rivers in Present and Future Climate

Data Processing on Graphs

North Adriatic Hydrogen Valley

Data Governance and Intellectual Property Governance in Common European Data Spaces – DGIP-CEDS

Latest Research Papers

Digital Twin-Driven Federated Learning and Reinforcement Learning-Based Offloading for Energy-Efficient Distributed Intelligence in IoT Networks

Forecasting the Trajectory of Personal Watercrafts Using Models Based on Recurrent Neural Networks

A System for Real-Time Detection of Abandoned Luggage

Enhancing Biophysical Muscle Fatigue Model in the Dynamic Context of Soccer

Pravna tehnologija (Legal Tech) i njezina (ne)prikladnost za zamjenu pravne struke

Latest News

Invited lecture: “About the first GPS receiver on the Moon, and the other NASA space PNT stories” by James J. Miller (NASA)

Agreement on collaboration between the Faculty of Engineering in Rijeka and the Shanghai Artificial Intelligence Research Institute

Arian Skoki defended his doctoral thesis “Data-Driven Assessment of Player Performance and Recovery in Soccer”

Anna Maria Mihel defended her PhD dissertation topic

Prof. dr. sc. Renato Filjar participated at the meeting of the 31st National Space-Based Positioning, Navigation and Timing US Advisory Board

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