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Obtaining statistical data

Sašo Pavlič

Sašo Pavlič
no.: 40983 source: SICRIS

active – not included in ARIS records
saso.pavlicat signstudent.um.si
  • English
  • Reading: Fluent
  • Writing: Fluent
  • Speaking: Fluent
  • Croatian
  • Reading: Functional
  • Writing: Basic
  • Speaking: Functional
  • Serbian
  • Reading: Functional
  • Writing: Basic
  • Speaking: Functional
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Research activity

Code Science Field Subfield
2.07.07  Engineering sciences and technologies  Computer science and informatics  Intelligent systems - software 
2.07.00  Engineering sciences and technologies  Computer science and informatics   
Keywords
The research area broadly encompasses the field of machine learning, and more specifically the area of artificial neural networks (or deep learning), various advanced architectures of these neural networks, advanced and innovative techniques for optimizing (training) these neural networks, and the application of such neural networks to problems of semi-supervised and unsupervised learning. Recently, advanced architectures of deep neural networks (autoencoders) have shown very good success in anomaly detection and other features in data. However, such advanced architectures have not yet been thoroughly tested in combination with advanced network optimization techniques using algorithms inspired by nature.
Bibliography Representative bibliographic units | Personal| COBISS+
source: COBISS
source: SICRIS
Evaluation (rules)
Evaluation of bibliographic research performance indicators according to ARIS methodology
source: COBISS
source: ARIS
Points
44.12
A''
0
A'
0
A1/2
0
CI10
0
CImax
0
h10
0
A1
0.12
A3
0
Data for the last 5 years (citations for the last 10 years) on June 27, 2024; A3 for period 2018-2022 (update for tender in 2023: NO)
Data for ARIS tenders ( 21.05.2024 – Target research programmes, archive )
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Database Linked records Citations Pure citations Average pure citations
WoS 1  0  0  0 
Scopus 3  1  0  0 
Education
source: SICRIS
Level of education Professional title Study subject Faculty Year
1st cycle bachelor's degree    Engineering in Computer Science and Communication Technologies  SI University of Maribor, Faculty of Electrical Engineering, Computer Science, and Informatics 2019 
2nd cycle master's degree  Master of Engineering in Computer Science and Communication Technologies  Computer Science and Communication Technologies  SI University of Maribor, Faculty of Electrical Engineering, Computer Science, and Informatics 2021 
Doctoral dissertations and other final papers Show
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source: COBISS
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