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News

Predicting Seagoing Ship Energy Efficiency from the Operational Data

19.04.2021

This paper presents the application of machine learning (ML) methods in setting up a model with the aim of predicting the energy efficiency of seagoing ships in the case of a vessel for the transport of liquefied petroleum gas (LPG). The ML algorithm is learned from shipboard automation system measurement data, noon logbook reports, and […]

Particle-Swarm-Optimization-Enhanced Radial-Basis- Function-Kernel-Based Adaptive Filtering Applied to Maritime Data

18.04.2021

The real-life signals captured by different measurement systems (such as modern maritime transport characterized by challenging and varying operating conditions) are often subject to various types of noise and other external factors in the data collection and transmission processes. Therefore, the filtering algorithms are required to reduce the noise level in measured signals, thus enabling […]

Prof. dr. sc. Todorka Glushkova held a talk on “Cyber-Physical Production Systems (CPPS)”

14.04.2021

Prof. dr. sc. Todorka Glushkova from the Faculty of Mathematics and Informatics, Paisii Hilendarski Plovdiv University, Plovdiv, Bulgaria, held an interesting presentation on “Cyber-Physical Production Systems (CPPS)” on the 14th of April, 2021. The presentation also addressed her work in the field and research interests with potentials for further collaboration.

RANSAC-Based Signal Denoising Using Compressive Sensing

01.04.2021

In this paper, we present an approach to the reconstruction of signals exhibiting sparsity in a transformation domain, having some heavily disturbed samples. This sparsity-driven signal recovery exploits a carefully suited random sampling consensus (RANSAC) methodology for the selection of a subset of inlier samples. To this aim, two fundamental properties are used: A signal […]

Presentation of prof. S. Martinčić-Ipšić and prof. Ana Meštrović

31.03.2021

Prof. dr. sc. Sanda Martinčić-Ipšić and prof. dr. sc. Ana Meštrović held an interesting talks on 31st of March, 2021 presenting their work in the field of applications of artificial intelligence to natural language processing and social network analysis. Recording of the presentations:

Summer School on Image Processing, 8-17 July 2021, Rijeka, Croatia

24.03.2021

29th Summer School on Image Processing – The annual gathering of researchers and professionals dealing with image analysis and machine vision. Rijeka, Croatia, 8-17 July 2021.

Post covering our latest research published online

22.03.2021

A news post has been published online about our latest published research regarding AI modelling of nanoscale friction.

Featured article about our research

22.03.2021

An article about our research has been published on Tribonet.org portal concerning nanoscale friction modelling using AI.

News published about our research

22.03.2021

An article about our research has been published on ScienceX portal.

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, […]

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Latest Projects

Knowledge Graphs in the Era of Large Language Models (KGELL)

LIVE Quantum – Development of an Integrated AI Platform for Multichannel Personalized Management of User Requests

Predicting Anomalous Trajectories Using Machine Learning

Adaptive Algorithms for Integrating Compressive Sensing with Deep Learning

Deep Learning for Smart Energy Systems Management

Latest Research Papers

Deep Unfolding ADMM Network for CS Image Reconstruction with Long-Short Term Residuals

XDT-FMARL: An Explainable Federated Multi-Agent Reinforcement Learning Framework for Energy-Efficient IoT Task Offloading

Proactive Context Aware Task Offloading in Digital Twin Driven Federated IoT Systems with Large Language Models

Pretraining and evaluation of BERT models for climate research

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

Latest News

Knowledge Graphs in the Era of Large Language Models (KGELL)

LIVE Quantum – Development of an Integrated AI Platform for Multichannel Personalized Management of User Requests

LIVE Quantum project kick-off meeting

Pretraining and evaluation of BERT models for climate research

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

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Center for Artificial Intelligence and Cybersecurity
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University of Rijeka

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