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Center for Artificial Intelligence and Cybersecurity – AIRI

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Laboratory for Data Mining, Open and Big Data

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

28.04.2022

Bottom-Up Design Approach for OBOC Peptide Libraries

28.07.2020

Design of short catalytic peptides and peptide assemblies (DeShPet)

01.02.2020

Institution: University of Rijeka, Department of Biotechnology

Applying Machine Learning for the Discovery of Peptides with Catalytic Activity

01.01.2020

Institution: Faculty of Engineering, University of Rijeka Objective: The aim of this project proposal is to build a catalytic activity prediction model for peptides that would drive a smart exploration of huge chemical search space.

Algorithm-supported, mass and sequence diversity-oriented random peptide library design

28.03.2019

Random peptide libraries that cover large search spaces are often used for the discovery of new binders, even when the target is unknown. To ensure an accurate population representation, there is a tendency to use large libraries. However, parameters such as the synthesis scale, the number of library members, the sequence deconvolution and peptide structure […]

Co-evolutionary Multi-Population Genetic Programming for Classification in Software Defect Prediction: an Empirical Case Study

05.06.2017

Evolving diverse ensembles using genetic programming has recently been proposed for classification problems with unbalanced data. Population diversity is crucial for evolving effective algorithms. Multilevel selection strategies that involve additional colonization and migration operations have shown better performance in some applications. Therefore, in this paper, we are interested in analysing the performance of evolving diverse ensembles using […]

A Systematic Data Collection Procedure for Software Defect Prediction

13.01.2016

Software defect prediction research relies on data that must be collected from otherwise separate repositories. To achieve greater generalization of the results, standardized protocols for data collection and validation are necessary. This paper presents an exhaustive survey of techniques and approaches used in the data collection process. It identifies some of the issues that must […]

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Latest Projects

ABsistemDCiCloud

Machine Learning for Knowledge Transfer in Medical Radiology

Estimating River Discharges in Highly Stratified Estuaries

Multilayer Framework for the Information Spreading Characterization in Social Media during the COVID-19 Crisis (InfoCoV)

European Network for assuring food integrity using non-destructive spectral sensors

Latest Research Papers

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

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

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

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

Improved Parametrized Multiple Window Spectrogram with Application in Ship Navigation Systems

Latest News

Assoc. prof. Jonatan Lerga received the Croatian Academy of Sciences and Arts award

Dr. Sc. Nikola Lopac successfully defended his doctoral dissertation

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

Assoc. prof. dr. sc. Jonatan Lerga presented AIRI Center at the IEEE Rijeka : Computer Society Congress 2021

Prof. dr. sc. Ana Mestrovic participated at the Panel on perspectives and real-life applications of AI organized by IEEE Technology and Engineering Management Society

We provide the expertise for solving real world problems using AI

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