Development of computational algorithms based on digital signal processing and artificial intelligence methods with application in modern transport systems
INNO2MARE – Strengthening the capacity for excellence of Slovenian and Croatian innovation ecosystems to support the digital and green transitions of maritime regions
Regression-Based Machine Learning Approaches for Estimating Discharge from Water Levels in Microtidal Rivers
Estimating Water Levels and Discharges in Tidal Rivers and Estuaries: Review of Machine Learning Approaches
Building Individual Player Performance Profiles According to Pre-Game Expectations and Goal Difference in Soccer
Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes
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
Detection of Non-Stationary GW Signals in High Noise from Cohen’s Class of Time-Frequency Representations Using Deep Learning
Particle-Swarm-Optimization-Enhanced Radial-Basis- Function-Kernel-Based Adaptive Filtering Applied to Maritime Data
Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of Intersection of Confidence Intervals Rule
Comparison of Entropy and Dictionary Based Text Compression in English, German, French, Italian, Czech, Hungarian, Finnish, and Croatian
Improving the Performance of Dynamic Ship Positioning Systems: A Review of Filtering and Estimation Techniques
Improved Power System State Estimator With Preprocessing Based on the Modified Intersection of Confidence Intervals
Adaptive Filtering and Analysis of EEG Signals in the Time-Frequency Domain Based on the Local Entropy
Extraction of Useful Information Content From Noisy Signals Based on Structural Affinity of Clustered TFDs’ Coefficients
