Ponedeljkov seminar računalništva in informatike - Arhiv

V ponedeljek, 23. maja 2022, bo ob 16.00 uri v predavalnici FAMNIT-VP2 izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 23. maj 2022 ob 16.00 v FAMNIT-VP2

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PREDAVATELJICA: prof. Amira ŠERIFOVIĆ TRBALIĆ
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Amira Šerifović Trbalić was born in Tuzla, Bosnia and Herzegovina in 1978. She received her B.Sc. degree from the Faculty of Electrical Engineering, University of Tuzla, Bosnia and Herzegovina in 2002. In 2006, she received the M.Sc. degree in computer science at the Faculty of Electrical Engineering, University of Tuzla. She finished her doctoral thesis on medical image registration at the University of Tuzla in 2011. Research for the doctoral dissertation was conducted within the framework of the joint research project with the Computer Vision Lab, ETH Zurich, Switzerland. In 2012, she became an Assistant Professor at the University of Tuzla and was promoted to Associate Professor in 2018. Her research interests include image processing and analysis, pattern recognition, computer vision and artificial intelligence. As a principal investigator or as a participant, she was involved in many projects in these areas and published over 40 research papers, books and book chapter.

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NASLOV: Applications of deep learning for the medical data analysis
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POVZETEK:

This talk will present an overview of deep learning (DL) and discuss some recent successful applications in medicine. It will provide examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, time series analysis, medical data synthesis and pre-processing operations. The talk will conclude with a discussion of relevant deep learning methods and their strengths and limitations.

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Vabljeni! 

V ponedeljek, 16. maja 2022, bo ob 16.00 uri prek spletnih orodij na daljavo izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 16. maj 2022 ob 16.00 na daljavo

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PREDAVATELJ: Vanja MILESKI
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After graduating from the Faculty of Computer and Information Science at the University of Ljubljana in 2015, Vanja Mileski started working at the Jožef Stefan Institute (JSI). He was a Master's student at the International Postgraduate School Jožef Stefan and a student researcher at the JSI. After finishing his Master's studies, he applied his knowledge of data mining in the private sector as a Data Scientist in the retail, telecommunications, banking, stock market and insurance sectors.
His current research interests include time-series classification, deep learning, ResNet and Inception architectures.

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NASLOV: Deep learning for time series data using Inception and ResNet paradigms
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POVZETEK:

With the advancements in Convolutional Neural Network (CNN) architectures such as Inception modules and ResNet architectures, it is of particular interest to study these advances and apply them on time series data. Time series features can be viewed as one-dimensional vectors, on which we can apply different types of filters using Inception modules, and then train a deeper network using a ResNet-like architecture. We propose an idea of combining these advancements and testing them on real-life data of customer shopping habits obtained from a large retailer in Slovenia with the hopes of beating traditional ML techniques.

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Vabljeni! 

V ponedeljek, 9. maja 2022, bo ob 16.00 uri prek spletnih orodij na daljavo izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 9. maj 2022 ob 16.00 na daljavo

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PREDAVATELJ: Jakob POVŠIČ
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Jakob Povšič je študent zadnjega letnikana dodiplomskega študijskega programa 1. stopnje Računalništvo in informatika na UP FAMNIT. Trenutno se posveča področjem decentraliziranih finančnih sistemov, in širše kriptovalut in digitalne identitete.

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NASLOV: Avtentikacija z dokazi ničelnega znanja
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POVZETEK:

Problematika zasebnosti je vsak dan večja zaradi vse večje prisotnosti informacijskih sistemov v naših življenjih. Zdi se, da se zasebnost in tehnologija medsebojno izključujeta. Dokazi ničelnega znanja (ZKP) imajo potencial, da spremenijo, kako naši osebni podatki obstajajo v digitalnem prostoru. Predstavljena bo preprosta uporaba ZKP kot metode preverjanja gesla v avtentikacijskem sistemu.

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Vabljeni!