The Laboratory for Information Processing and Pattern Recognition is, among the other, focused on research and knowledge transfer to and from industry in the fields of information processing, pattern recognition, signal processing, image, and video analysis, information theory, coding, and cryptography.
Head of Laboratory
Laboratory Projects
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
European Digital Innovation Hub Adria Croatia
ABsistemDCiCloud
Estimating River Discharges in Highly Stratified Estuaries
National Competence Centres in the Framework of EuroHPC (EUROCC)
Hyperspectral Image Analysis Using Machine Learning and Adaptive Data-Driven Filtering
Development of machine-learning-based techniques for illness and injury detection in medical images
Computer-Aided Digital Analysis And Classification of Signals
A Network for Gravitational Waves, Geophysics and Machine Learning
Laboratory Research Papers
Regression-Based Machine Learning Approaches for Estimating Discharge from Water Levels in Microtidal Rivers
Method for Automatic Estimation of Instantaneous Frequency and Group Delay in Time–Frequency Distributions with Application in EEG Seizure Signals Analysis
Sparse Time-Frequency Distribution Reconstruction Using the Adaptive Compressed Sensed Area Optimized with the Multi-Objective Approach
Block-Adaptive Rényi Entropy-Based Denoising for Non-Stationary Signals
Application of Laser Systems for Detection and Ranging in the Modern Road Transportation and Maritime Sector
Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes
Improved Parametrized Multiple Window Spectrogram with Application in Ship Navigation Systems
BlueNavi: A Microservices Architecture-Styled Platform Providing Maritime Information
Shipboard Data Compression Method for Sustainable Real-Time Maritime Communication in Remote Voyage Monitoring of Autonomous Ships
Detection of Non-Stationary GW Signals in High Noise from Cohen’s Class of Time-Frequency Representations Using Deep Learning
Analysis of Cryptography Algorithms Implemented in Android Mobile Application
Modeling Uncertainty in Fracture Age Estimation from Pediatric Wrist Radiographs
Multivariate Decomposition of Acoustic Signals in Dispersive Channels
From Time–Frequency to Vertex–Frequency and Back
Particle-Swarm-Optimization-Enhanced Radial-Basis- Function-Kernel-Based Adaptive Filtering Applied to Maritime Data
RANSAC-Based Signal Denoising Using Compressive Sensing
Rule-Based EEG Classifier Utilizing Local Entropy of Time–Frequency Distributions
Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of Intersection of Confidence Intervals Rule
Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification
Comparison of Entropy and Dictionary Based Text Compression in English, German, French, Italian, Czech, Hungarian, Finnish, and Croatian
A Novel Approach to Extracting Useful Information From Noisy TFDs Using 2D Local Entropy Measures
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
Automatic Music Transcription for Traditional Woodwind Instruments Sopele
Brain Computer Interface Based Communicator for Persons in Locked-in State
Extraction of Useful Information Content From Noisy Signals Based on Structural Affinity of Clustered TFDs’ Coefficients
Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection
Support Vector Machine State Estimation
Adaptive State Estimator With Intersection of Confidence Intervals Based Preprocessing
Adaptive Methods for Video Denoising Based on the ICI, FICI, and RICI Algorithms
An Adaptive Method Based on the Improved LPA-ICI Algorithm for MRI Enhancement
Mirroring Quasi-Symmetric Organ Observations for Reducing Problem Complexity
A Fast Signal Denoising Algorithm Based on the LPA-ICI Method for Real-Time Applications
Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
Improved LPA-ICI-Based Estimators Embedded in a Signal Denoising Virtual Instrument
Affiliated Researchers
- Jonatan Lerga, Assist. Prof., PhD (RITEH)
- Anna Maria Mihel, mag. ing. comp. (RITEH)
- Arian Skoki, mag. ing. comp. (RITEH)
- Ana Vranković, mag. ing. comp. (RITEH)
- Boris Gašparović, mag. ing. comp. (RITEH)
- David Bačnar, Asist. mag. ing. el. (RITEH)
- Denis Selimović, mag. ing. el. (RITEH)
- Guruprasad Madhale Jadav (RITEH)
- Jude Hermant (external)
- Karlo Severinski, mag. ing.
- Luka Batistić, mag. ing. comp. (RITEH)
- Milan Budimir, mag. ing.
- Mladen Tomić, Assoc. Prof., PhD (RITEH)
- Marinko Žagar, sen. lect.
- Nikola Lopac, Assist. Prof., PhD (PFRI)
- Veljko Jardas, mag. ing. el.
