Maja Braović
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Artificial Intelligence-Based Prediction Model for Maritime Vessel Type Identification Open
This paper presents an artificial intelligence-based model for the classification of maritime vessel images obtained by cameras operating in the visible part of the electromagnetic spectrum. It incorporates both the deep learning technique…
Exploring Applications of Convolutional Neural Networks in Analyzing Multispectral Satellite Imagery: A Systematic Review Open
Remote sensing is of great importance for analyzing and studying various phenomena occurrence and development on Earth. Today is possible to extract features specific to various fields of application with the application of modern machine …
Multi-Label Confusion Tensor Open
The confusion matrix is the tool commonly used for the evaluation of the performance of a classification algorithm. While the computation of the confusion matrix for multi-class classification follows a well-developed procedure, the common…
A Systematic Review of Computational Approaches to Deciphering Bronze Age Aegean and Cypriot Scripts Open
This article provides a detailed insight into computational approaches for deciphering Bronze Age Aegean and Cypriot scripts, namely, the Archanes script and the Archanes formula, Phaistos Disk, Cretan hieroglyphic (including the Malia Alt…
Performance Comparison of the Cogent Confabulation Classifier with Other Commonly Used Supervised Machine Learning Algorithms for Bathing Water Quality Assessment Open
The purpose of this study was to implement a reliable model for bathing water quality prediction using the Cogent Confabulation classifier and to compare it with other well-known classifiers. This study is a continuation of a previously pu…
Data Analysis of the Web News Headlines based on Natural Language Processing Open
This paper explores the problem of media content data analysis with the focus on the phenomenon of vaccination, closely related to the COVID-19 pandemic. The presented research is an extension of the previous work, but it differs in two ma…
Semantic Conceptual Framework for Environmental Monitoring and Surveillance—A Case Study on Forest Fire Video Monitoring and Surveillance Open
This paper presents a semantic conceptual framework and definition of environmental monitoring and surveillance and demonstrates an ontology implementation of the framework. This framework is defined in a mathematical formulation and is bu…
Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images Open
In this paper, we describe a method for the prediction of concentration of chlorophyll-a (Chl-a) from satellite data in the coastal waters of Kaštela Bay and the Brač Channel (our case study areas) in the Republic of Croatia. Chl-a is one …
Deep learning based approach for optic disc and optic cup semantic segmentation for glaucoma analysis in retinal fundus images Open
Optic disc and optic cup are one of the most recognized retinal landmarks, and there are numerous methods for their automatic detection. Segmented optic disc and optic cup are useful in providing the contextual information about the retina…
Multi-label Classifier Performance Evaluation with Confusion Matrix Open
Confusion matrix is a useful and comprehensive presentation of the classifier performance.It is commonly used in the evaluation of multi-class, single-label classification models, where each data instance can belong to just one class at an…
Convolutional Neural Networks and Transfer Learning Based Classification of Natural Landscape Images Open
Natural landscape image classification is a difficult problem in computer vision. Many classes that can be found in such images are often ambiguous and can easily be confused with each other (e.g. smoke and fog), and not just by a computer…
Retinal blood vessel segmentation based on heuristic image analysis Open
Automatic analysis of retinal fundus images is becoming increasingly present today, and diseases such as diabetic retinopathy and age-related macular degeneration are getting a higher chance of being discovered in the early stages of their…
Non-parametric context-based object classification in images Open
Segmentation and classification of objects in images is one of the mostimportant and yet one of the most complex problems in computer vision. Manydifferent things contribute to the complexity of this problem, but amongst thosethat are most…
Cogent Confabulation based Expert System for Segmentation and Classification of Natural Landscape Images Open
Ever since there has been an increase in the number of automatic wildfire monitoring and surveillance systems in the last few years, natural landscape images have been of great importance. In this paper we propose an expert system for fast…