Ponedeljkov seminar računalništva in informatike - Arhiv

Danes, v ponedeljek, 27. septembra 2021, 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: 27. september 2021 ob 16.00 na daljavo

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PREDAVATELJ: Nedim ŠIŠIĆ
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Nedim Šišić is a first year student of the master programme in Computer Science at UP FAMNIT. He will be presenting his Research seminar that he completed under the supervision of prof. Martin Milanič.

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NASLOV: A new method for polygonization of connected areas in binary images
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POVZETEK:

In image processing, vectorization is the conversion of raster images to vector images. Polygonization, a type of vectorization, finds polygonal approximations of raster images. Most existing vectorization methods process entire images, thus performing unnecessary work if we are only interested in a single part of an image. Here, we will describe an approach to polygonizing binary images, where only a single connected component of interest is polygonized. Our method reduces the time and space requirements in this problem setting compared to existing methods. In this presentation we will show the results of the proposed method, Polygonize.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Vabljeni! 

V ponedeljek, 20. septembra 2021, 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: 20. september 2021 ob 16.00 na daljavo

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PREDAVATELJ: Jordan DEJA
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Jordan Aiko Deja is a Filipino PhD student working on computational interactions and adaptive visualizations at the HICUP Lab research group of UP FAMNIT. He is supervised by Dr. Matjaž Kljun and Dr. Klen Čopič Pucihar. He earned his BS and MS degrees in Computer Science from De La Salle University, Manila Philippines.

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NASLOV: PIANO 2.0: An Augmented Piano prototype for Personalized Music Learning
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POVZETEK:

Humans have been developing, learning and playing musical instruments for several millennia. With technological advancements, instruments were becoming more complex. However, it is in the recent decades, that several computer supported innovations augmenting musical instruments have been introduced. In this seminar, we present PIANO 2.0 - with the goal of augmenting the music learning experience of a piano novice. We will present the proposed design, a demonstration of its existing features and a proposed user testing plan. We will solicit ideas from the audience in order to improve the prototype design, and the proposed data collection and user testing plan intended for piano learners.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Vabljeni!

V ponedeljek, 13. septembra 2021, 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: 13. september 2021 ob 16.00 na daljavo

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PREDAVATELJICA: Elham MOTAMEDI
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Elham Motamedi is a PhD student at UP FAMNIT under the supervision of prof. Marko Tkalčič. She completed her Master's degree of networked systems at the University of Tehran, Iran and her Bachelor's degree of information technology at the Isfahan University of Technology, Iran. Her research areas include recommender systems,  machine learning and complex networks.

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NASLOV: Prediction of eudaimonic and hedonic movie characteristics from subtitles
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POVZETEK:

In this work, I will present the pipeline and preliminary results for the prediction of eudaimonic and hedonic characteristics of movies. First, I will provide a motivation why these characteristics are important for personalization (user modeling and recommender systems). Then I will briefly present the dataset that we used with focussing on the correlational analysis of the data. Then I will describe the machine learning pipeline, from using natural language processing techniques for feature engineering to the training and evaluation. Finally, I will present the results of the prediction.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Vabljeni!

V ponedeljek, 6. septembra 2021, 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: 6. september 2021 ob 16.00 na daljavo

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PREDAVATELJ: Nuwan T. ATTYGALLE
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Nuwan Tharanga Attygalle is a PhD student in Computer Science in the field of Human-Computer interactions and a teaching assistant at the University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies. He is also a member of the HICUP Lab at the Department of Information Sciences and Technologies.

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NASLOV: Interactive Web Documentaries: A Case Study of Video Viewing Behaviour on iOtok
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POVZETEK:

In this study, we explore video viewing behaviour when videos are wrapped in interactive content in the case of iOtok, a 13-episodes web documentary series. The interaction and viewing data were collected over a period of one year, providing a dataset of more than 12200 total video views by 6000 users. Standard metrics (video views, percentage viewed, number of sessions) show higher active participation for registered users compared to unregistered users. Results also indicate that serialisation over multiple weeks is an effective strategy for audience building over a long period of time without negatively affecting video views. In viewing behaviour analysis, we focused on three perspectives: (i) regularity (watching on a weekly basis or not), (ii) intensity (number of videos per session) and (iii) order of watching. We performed a perspective based and combined perspectives analysis involving manual coding techniques, rule-based and k-means clustering algorithms to reveal different user profiles (intermittent, exemplary, detached, enthusiastic users, and nibblers) and highlight further viewing behaviour differences (e.g. post-series users binge-watched more than concurrent users during first 13 weeks while the series was weekly released). We discuss how these results can be used to inform the design and promotion of future web documentaries.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Vabljeni!