CEEPUS network “International Cooperation in Computer Science”, CIII-HU-0019-14-1819, (2018-ongoing) The project is conducted at the Faculty of Engineering, University of Rijeka (www.riteh.uniri.hr).
Laboratory for Information Processing and Pattern Recognition
A Network for Gravitational Waves, Geophysics and Machine Learning
The breakthrough discovery of gravitational waves on September 14, 2015 was made possible through synergy of techniques drawing from expertise in physics, mathematics, information science and computing. At present, there is a rapidly growing interest in Machine Learning (ML), Deep Learning (DL), classification problems, data mining and visualization and, in general, in the development of […]
Adaptive Methods for Video Denoising Based on the ICI, FICI, and RICI Algorithms
In various applications, reducing noise from video sequence is of crucial importance. In this paper, we have presented performance analysis of the novel video denoising method based on the relative intersection of confidence intervals (RICI) rule, and compared it to the methods based on the intersection of confidence intervals (ICI) rule and the fast ICI […]
Primorje-Gorski Kotar County Award in 2018 for J. Lerga
Assist. Professor Jonatan Lerga received an annual award from Primorje-Gorski Kotar County, Croatia, in 2018.
An Adaptive Method Based on the Improved LPA-ICI Algorithm for MRI Enhancement
Various diseases are diagnosed using medical imaging used for analysing internal anatomical structures. However, medical images are susceptible to noise introduced in both acquisition and transmission processes. We propose an adaptive data-driven image denoising algorithm based on an improvement of the intersection of confidence intervals (ICI), called relative ICI (RICI) algorithm. The 2D mask of […]
Mirroring Quasi-Symmetric Organ Observations for Reducing Problem Complexity
Following an obvious growth of available collections of medical images in recent years, both in number and in size, machine learning has nowadays become an important tool for solving various image-analysis-related problems, such as organ segmentation or injury/pathology detection. The potential of learning algorithms to produce models having good generalisation properties is highly dependent on […]
A Fast Signal Denoising Algorithm Based on the LPA-ICI Method for Real-Time Applications
We propose a new algorithm for denoising of additive white Gaussian noise-corrupted signals, based on the intersection of confidence intervals (ICI) algorithm, called the fast intersection of confidence intervals (FICI) algorithm. The proposed approach combines the FICI algorithm, used for the adaptive filter support size selection, with the local polynomial approximation (LPA) method, used as […]
Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its […]
Improved LPA-ICI-Based Estimators Embedded in a Signal Denoising Virtual Instrument
Adaptive filters embedded in a user-friendly virtual instrument (VI) for signal denoising are proposed in the paper. The filters are based on the local polynomial approximation (LPA) and equipped with the improved intersection of confidence intervals (ICI) rule, known as the relative intersection of confidence intervals (RICI) rule, in order to achieve adaptivity to high […]
