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Research Papers

Block-Adaptive Rényi Entropy-Based Denoising for Non-Stationary Signals

28.10.2022

This paper approaches the problem of signal denoising in time-variable noise conditions. Non-stationary noise results in variable degradation of the signal’s useful information content over time. In order to maximize the correct recovery of the useful part of the signal, this paper proposes a denoising method that uses a criterion based on amplitude segmentation and […]

Emphasis on Occupancy Rates in Carbon Emission Comparison for Maritime and Road Passenger Transportation Modes

31.08.2022

Carbon emissions generated by the transportation sector represent a large part of total greenhouse gas emissions and are thus subject to various policies and initiatives for emission reduction and the development of sustainable transportation networks. Furthermore, passenger transportation generates a significant amount of emissions within this sector, especially in those countries with large and developed […]

On the use and abuse of Big Data in competitive markets – Possible challenges for competition law

31.08.2022

Application of Laser Systems for Detection and Ranging in the Modern Road Transportation and Maritime Sector

09.08.2022

The development of light detection and ranging (lidar) technology began in the 1960s, following the invention of the laser, which represents the central component of this system, integrating laser scanning with an inertial measurement unit (IMU) and Global Positioning System (GPS). Lidar technology is spreading to many different areas of application, from those in autonomous […]

Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning

15.06.2022

Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have witnessed an impressive progress on both of these problems, giving rise to a new family of approaches. Especially, the advances in deep learning over the past couple of years have led […]

Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes

13.05.2022

This paper explores three groups of time–frequency distributions: the Cohen’s, affine, and reassigned classes of time–frequency representations (TFRs). This study provides detailed insight into the theory behind the selected TFRs belonging to these classes. Extensive numerical simulations were performed with examples that illustrate the behavior of the analyzed TFR classes in the joint time–frequency domain. […]

Coupled encoding methods for antimicrobial peptide prediction: How sensitive is a highly accurate model?

28.04.2022

The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data

18.03.2022

Non-stationary signals are often analyzed using raw waveform data or spectrograms of those data; however, the possibility of alternative time–frequency representations being more informative than the original data or spectrograms is yet to be investigated. This paper tested whether alternative time–frequency representations could be more informative for machine learning classification of seismological data. The mentioned […]

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 […]

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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

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

Regression-Based Machine Learning Approaches for Estimating Discharge from Water Levels in Microtidal Rivers

Latest News

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

Presentation of the NPOO project Peoplet

Ana Vranković Lacković defended her doctoral thesis

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Center for Artificial Intelligence and Cybersecurity
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