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1.
Beleženje delovnega časa zaposlenih s tehnologijo geo-ograjevanja
Nejc Planer, 2024, magistrsko delo

Opis: V magistrskem delu raziščemo rešitve za beleženje časa zaposlenih in tehnologijo geo-ograjevanja. Predstavimo razvoj spletne in mobilne aplikacije za beleženje časa zaposlenih, kjer tudi predstavimo uporabo tehnologije geo-ograjevanja za avtomatsko beleženje časa. Na podlagi razvite rešitve smo izvedli anketo in predstavili rezultate uporabnosti spletne aplikacije ter tehnologije geo-ograjevanja za avtomatsko beleženje časa v pisarniških prostorih.
Ključne besede: geo-ograjevanje, beleženje časa zaposlenih, avtomatsko beleženje časa
Objavljeno v DKUM: 01.07.2024; Ogledov: 65; Prenosov: 6
.pdf Celotno besedilo (3,11 MB)

2.
3.
Graph Neural Network-Based Method of Spatiotemporal Land Cover Mapping Using Satellite Imagery
Domen Kavran, Domen Mongus, Borut Žalik, Niko Lukač, 2023, izvirni znanstveni članek

Ključne besede: multispectral, Sentinel-2, superpixel, node, EfficientNetV2, GraphSAGE
Objavljeno v DKUM: 23.05.2024; Ogledov: 128; Prenosov: 7
.pdf Celotno besedilo (34,47 MB)
Gradivo ima več datotek! Več...

4.
Spletna aplikacija za vodenje oskrbovalne verige z uporabo ogrodij Vue.js in Laravel
Andrej Ouček, 2024, diplomsko delo

Opis: 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.
Ključne besede: spletna aplikacija, ogrodje Laravel, ogrodje Vue.js, PHP, programiranje
Objavljeno v DKUM: 22.05.2024; Ogledov: 209; Prenosov: 22
.pdf Celotno besedilo (2,23 MB)

5.
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, izvirni znanstveni članek

Opis: 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.
Ključne besede: computer science, algorithm, string transformation, information entropy, Hilbert space filling curve
Objavljeno v DKUM: 22.05.2024; Ogledov: 109; Prenosov: 7
.pdf Celotno besedilo (26,44 MB)
Gradivo ima več datotek! Več...

6.
7.
CNN-Based Vessel Meeting Knowledge Discovery From AIS Vessel Trajectories
Peng Chen, Shuang Liu, Niko Lukač, 2023, izvirni znanstveni članek

Opis: 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.
Ključne besede: AIS Data, CNN, Dynamic Rammer-Douglas-Peucker, knowledge discovery, maneuvering pattern, traffic pattern, trajectory
Objavljeno v DKUM: 19.03.2024; Ogledov: 487; Prenosov: 416
.pdf Celotno besedilo (3,84 MB)
Gradivo ima več datotek! Več...

8.
9.
Novel Half-Spaces Based 3D Building Reconstruction Using Airborne LiDAR Data
Marko Bizjak, Domen Mongus, Borut Žalik, Niko Lukač, 2023, izvirni znanstveni članek

Opis: 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.
Ključne besede: LiDAR point cloud, building reconstruction, half-spaces, Boolean operations
Objavljeno v DKUM: 01.12.2023; Ogledov: 325; Prenosov: 19
.pdf Celotno besedilo (13,79 MB)
Gradivo ima več datotek! Več...

10.
Razvoj napovednega modela multivariatnih časovnih vrst uporabniških storitev : diplomsko delo
Sandi Pečečnik, 2023, diplomsko delo

Opis: 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.
Ključne besede: časovne vrste, nevronske mreže, globoko učenje, storitve, arhitekture globokega učenja
Objavljeno v DKUM: 05.10.2023; Ogledov: 410; Prenosov: 30
.pdf Celotno besedilo (1,66 MB)

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