| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Search the digital library catalog Help

Query: search in
search in
search in
search in
* old and bologna study programme

Options:
  Reset


1 - 10 / 64
First pagePrevious page1234567Next pageLast page
1.
2.
Graph Neural Network-Based Method of Spatiotemporal Land Cover Mapping Using Satellite Imagery
Domen Kavran, Domen Mongus, Borut Žalik, Niko Lukač, 2023, original scientific article

Keywords: multispectral, Sentinel-2, superpixel, node, EfficientNetV2, GraphSAGE
Published in DKUM: 23.05.2024; Views: 56; Downloads: 1
.pdf Full text (34,47 MB)
This document has many files! More...

3.
Spletna aplikacija za vodenje oskrbovalne verige z uporabo ogrodij Vue.js in Laravel
Andrej Ouček, 2024, undergraduate thesis

Abstract: V diplomskem delu je predstavljen proces načrtovanja, razvoja in implementacije spletne aplikacije za poenostavitev delovnih procesov in digitalizacijo, izdelane posebej za potrebe izbranega podjetja. S pomočjo te aplikacije lahko podjetje zdaj učinkoviteje upravlja z internimi procesi, kar vodi k večji produktivnosti in manjšim možnostim napak. Za razvoj spletne aplikacije smo uporabili ogrodji Laravel in Vue.js, ki omogočata učinkovito delovanje, skalabilnost in enostavno vzdrževanje sistema.
Keywords: spletna aplikacija, ogrodje Laravel, ogrodje Vue.js, PHP, programiranje
Published in DKUM: 22.05.2024; Views: 62; Downloads: 12
.pdf Full text (2,23 MB)

4.
A new transformation technique for reducing information entropy : a case study on greyscale raster images
Borut Žalik, Damjan Strnad, David Podgorelec, Ivana Kolingerová, Luka Lukač, Niko Lukač, Simon Kolmanič, Krista Rizman Žalik, Štefan Kohek, 2023, original scientific article

Abstract: This paper proposes a new string transformation technique called Move with Interleaving (MwI). Four possible ways of rearranging 2D raster images into 1D sequences of values are applied, including scan-line, left-right, strip-based, and Hilbert arrangements. Experiments on 32 benchmark greyscale raster images of various resolutions demonstrated that the proposed transformation reduces information entropy to a similar extent as the combination of the Burrows–Wheeler transform followed by the Move-To-Front or the Inversion Frequencies. The proposed transformation MwI yields the best result among all the considered transformations when the Hilbert arrangement is applied.
Keywords: computer science, algorithm, string transformation, information entropy, Hilbert space filling curve
Published in DKUM: 22.05.2024; Views: 35; Downloads: 2
.pdf Full text (26,44 MB)
This document has many files! More...

5.
6.
CNN-Based Vessel Meeting Knowledge Discovery From AIS Vessel Trajectories
Peng Chen, Shuang Liu, Niko Lukač, 2023, original scientific article

Abstract: How to extract a collection of trajectories for different vessels from the raw AIS data to discover vessel meeting knowledge is a heavily studied focus. Here, the AIS database is created based on the raw AIS data after parsing, noise reduction and dynamic Ramer-Douglas-Peucker compression. Potential encountering trajectory pairs will be recorded based on the candidate meeting vessel searching algorithm. To ensure consistent features extracted from the trajectories in the same time period, time alignment is also adopted. With statistical analysis of vessel trajectories, sailing segment labels will be added to the input feature. All motion features and sailing segment labels are combined as input to one trajectory similarity matching method based on convolutional neural network to recognize crossing, overtaking or head-on situations for each potential encountering vessel pair, which may lead to collision if false actions are adopted. Experiments on AIS data show that our method is effective in classifying vessel encounter situations to provide decision support for collision avoidance.
Keywords: AIS Data, CNN, Dynamic Rammer-Douglas-Peucker, knowledge discovery, maneuvering pattern, traffic pattern, trajectory
Published in DKUM: 19.03.2024; Views: 406; Downloads: 408
.pdf Full text (3,84 MB)
This document has many files! More...

7.
8.
Novel Half-Spaces Based 3D Building Reconstruction Using Airborne LiDAR Data
Marko Bizjak, Domen Mongus, Borut Žalik, Niko Lukač, 2023, original scientific article

Abstract: Automatic building reconstruction from laser-scanned data remains a challenging research topic due to buildings’ roof complexity and sparse data. A novel automatic building reconstruction methodology, based on half-spaces and a height jump analysis, is presented in this paper. The proposed methodology is performed in three stages. During the preprocessing stage, the classified input point cloud is clustered by position to obtain building point sets, which are then evaluated to obtain half-spaces and detect height jumps. Half-spaces represent the fundamental shape for generating building models, and their definition is obtained from the corresponding segment of points that describe an individual planar surface. The detection of height jumps is based on a DBSCAN search within a custom search space. During the second stage, the building point sets are divided into sub-buildings in such a way that their roofs do not contain height jumps. The concept of sub-buildings without height jumps is introduced to break down the complex building models with height jumps into smaller parts, where shaping with half-spaces can be applied accurately. Finally, the sub-buildings are reconstructed separately with the corresponding half-spaces and then joined back together to form a complete building model. In the experiments, the methodology’s performance was demonstrated on a large scale and validated on an ISPRS benchmark dataset, where an RMSE of 0.29 m was obtained in terms of the height difference.
Keywords: LiDAR point cloud, building reconstruction, half-spaces, Boolean operations
Published in DKUM: 01.12.2023; Views: 276; Downloads: 19
.pdf Full text (13,79 MB)
This document has many files! More...

9.
Razvoj napovednega modela multivariatnih časovnih vrst uporabniških storitev : diplomsko delo
Sandi Pečečnik, 2023, undergraduate thesis

Abstract: V sklopu diplomskega dela predstavimo več nevronskih mrež, ki jih optimiziramo, pri čemer raziščemo ustrezne arhitekture, metrike, funkcije in druge pomembne lastnosti za uporabo v napovednih modelih multivariantnih časovnih vrst. Raziščemo najpomembnejše probleme povezane z razvojem napovednih nevronskih mrež. Naslovimo reševanje treh specifičnih realnih problemov, za reševanje katerih smo predlagali arhitekture nevronskih mrež. Izdelali smo še skalabilno spletno aplikacijo, ki omogoča enostavnejšo uporabo naučenih modelov nevronskih mrež.
Keywords: časovne vrste, nevronske mreže, globoko učenje, storitve, arhitekture globokega učenja
Published in DKUM: 05.10.2023; Views: 359; Downloads: 28
.pdf Full text (1,66 MB)

10.
Aplikacija za spreminjanje parametrov grafičnih procesnih enot : diplomsko delo
Žiga Tanacek, 2023, undergraduate thesis

Abstract: V diplomskem delu predstavimo aplikacijo za spreminjanje parametrov grafičnih procesnih enot (GPE). Poleg predstavitve razvoja opišemo sorodne aplikacije in aplikacije za merjenje uspešnosti spreminjanja parametrov GPE. Na kratko povzamemo tudi vse tehnologije, ki smo jih uporabili, in njihov razvoj. Za komunikacijo z grafičnimi procesnimi enotami predstavimo novo dinamično knjižnico, ki temelji na knjižnici AMD Display Library in na programskem jeziku C++. Za praktični primer uporabe dane knjižnice predstavimo uporabniško prijazen čelni del aplikacije, kjer uporabimo tehnologijo WPF.
Keywords: grafične procesne enote, parametri GPE, namizna aplikacija, WPF, C#
Published in DKUM: 05.10.2023; Views: 212; Downloads: 17
.pdf Full text (2,38 MB)

Search done in 0.23 sec.
Back to top
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica