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Center for Artificial Intelligence and Cybersecurity – AIRI

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Laboratory for Information Processing and Pattern Recognition

Improved Parametrized Multiple Window Spectrogram with Application in Ship Navigation Systems

03.03.2022

In analyzing non-stationary noisy signals with time-varying frequency content, it’s convenient to use distribution methods in joint, time and frequency, domains. Besides different adaptive data-driven time-frequency (TF) representations, the approach with multiple orthogonal and optimally concentrated Hermite window functions is an effective solution to achieve a good trade-off between low variance and minimized stable bias […]

BlueNavi: A Microservices Architecture-Styled Platform Providing Maritime Information

14.02.2022

Traditional methods of marine navigation are undergoing a revolution brought about by the almost universal adoption of the Automatic Identification System (AIS). AIS exchanges a wealth of navigational information among vessels and between ships to shore through Very High Frequency (VHF). With AIS data integrated into the Electronic Chart Display and Information System (ECDIS), the […]

Shipboard Data Compression Method for Sustainable Real-Time Maritime Communication in Remote Voyage Monitoring of Autonomous Ships

07.02.2022

Due to the ever-increasing amount of data collected and the requirements for the rapid and reliable exchange of information across many interconnected communication devices, land-based communications networks are experiencing continuous progress and improvement of existing infrastructures. However, maritime communications are still characterized by slow communication speeds and limited communication capacity, despite a similar trend of […]

Detection of Non-Stationary GW Signals in High Noise from Cohen’s Class of Time-Frequency Representations Using Deep Learning

31.12.2021

Analysis of non-stationary signals in a noisy environment is a challenging research topic in many fields often requiring simultaneous signal decomposition in the time and frequency domain. This paper proposes a method for the classification of noisy non-stationary time-series signals based on Cohen’s class of their time-frequency representations (TFRs) and deep learning algorithms. We demonstrated […]

Analysis of Cryptography Algorithms Implemented in Android Mobile Application

16.12.2021

This paper evaluates the performances of numerous encryption algorithms on mobile devices running the Android operating system. The primary objective of our research was to measure and compare the relative performances of tested algorithm implementations (Data Encryption Standard (DES), 3DES, Advanced Encryption Standard (AES), ChaCha20, Blowfish, and Rivest Cipher 4 (RC4)) on the Android platform. […]

Modeling Uncertainty in Fracture Age Estimation from Pediatric Wrist Radiographs

13.12.2021

In clinical practice, fracture age estimation is commonly required, particularly in children with suspected non-accidental injuries. It is usually done by radiologically examining the injured body part and analyzing several indicators of fracture healing such as osteopenia, periosteal reaction, and fracture gap width. However, age-related changes in healing timeframes, inter-individual variabilities in bone density, and […]

Presentation at the conference “Digital Innovation and Technology for People”

09.12.2021

Assoc. Prof. Dr. Sc. Jonatan Lerga held a talk on “How is AI Changing Financial Services?” at the conference “Digital Innovation and Technology for People” held in Opatija on the 9th of December 2021.

Multivariate Decomposition of Acoustic Signals in Dispersive Channels

04.11.2021

We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and processed individually, which carries opportunities for new insights into their characterization possibilities. The […]

From Time–Frequency to Vertex–Frequency and Back

17.06.2021

The paper presents an analysis and overview of vertex–frequency analysis, an emerging area in graph signal processing. A strong formal link of this area to classical time–frequency analysis is provided. Vertex–frequency localization-based approaches to analyzing signals on the graph emerged as a response to challenges of analysis of big data on irregular domains. Graph signals […]

ABsistemDCiCloud

30.04.2021

Kratki opis projekta Alarm automatika je u suradnji s Tehničkim fakultetom u Rijeci kroz istraživačko razvojne aktivnosti u području ekologije i sigurnosti osmislila proizvod koji je u isto vrijeme namijenjen zaštiti domova, poslovnih prostora te ostalih objekata i povećanju energetske učinkovitosti. ABsistemDCiCloud predstavlja inovaciju na tržištu koja se temelji na razvijenom softveru, a koja će […]

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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

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Center for Artificial Intelligence and Cybersecurity
  • jlerga@airi.uniri.hr
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