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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: 98; Downloads: 3
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3.
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: 81; Downloads: 6
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4.
5.
Implementacija SPIHT : magistrsko delo
Luka Kovačič, 2024, master's thesis

Abstract: V magistrskem delu najprej predstavimo Haarovo transformacijo. Nato razložimo pojme in podatkovne strukture, potrebne za razumevanje algoritma SPIHT. Predstavimo psevdokod implementacije kodiranja in dekodiranja. Delovanje pokažemo na primeru. Algoritem implementiramo in ga testiramo na različnih slikah. Učinkovitost stiskanja primerjamo s formati PNG, JPEG in JPEG 2000, ki se izkaže kot najučinkovitejši.
Keywords: SPIHT, drevesa prostorske orientacije, Haarova transformacija, rastrske slike, napredujoče stiskanje
Published in DKUM: 19.03.2024; Views: 195; Downloads: 38
.pdf Full text (2,43 MB)

6.
LiDAR-Based Maintenance of a Safe Distance between a Human and a Robot Arm
David Podgorelec, Suzana Uran, Andrej Nerat, Božidar Bratina, Sašo Pečnik, Marjan Dimec, Franc Žaberl, Borut Žalik, Riko Šafarič, 2023, original scientific article

Abstract: This paper focuses on a comprehensive study of penal policy in Slovenia in the last 70 years, providing an analysis of statistical data on crime, conviction, and prison populations. After a sharp political and penal repression in the first years after World War II, penal and prison policy began paving the way to a unique "welfare sanction system", grounded in ideas of prisoners' treatment. After democratic reforms in the early 1990s, the criminal legislation became harsher, but Slovenia managed to avoid the general punitive trends characterized by the era of penal state and culture of control. The authoritarian socialist regime at its final stage had supported the humanization of the penal system, and this trend continued in the first years of the democratic reforms in the 1990s, but it lost its momentum after 2000. In the following two decades, Slovenia experienced a continuous harshening of criminal law and sanctions on the one hand and an increasing prison population rate on the other. From 2014 onwards, however, there was a decrease in all segments of penal statistics. The findings of the study emphasize the exceptionalism of Slovenian penal policy, characterized by penal moderation, which is the product of the specific local historical, political, economic, and normative developments.
Keywords: LIDAR, robot, human-robot collaboration, speed and separation monitoring, intelligent control system, geometric data registration, motion prediction
Published in DKUM: 16.02.2024; Views: 316; Downloads: 18
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7.
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: 306; Downloads: 19
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8.
Vplivi transformacij MTF, IF in RS na informacijsko entropijo rastrskih slik z zveznimi barvnimi toni : diplomsko delo
Rene Vrbnjak Drozg, 2023, undergraduate thesis

Abstract: V diplomskem delu predstavimo algoritme transformacij nizov, in sicer: transformacija premik naprej, transformacija inverzne frekvence in transformacija desno manjše. Nize tvorimo iz sivin‐ skih rastrskih slik, pri čemer preizkusimo različne načine branja: branje z rastrskim prebiranjem, branje levo‐desno, branje cik‐cak, območno branje cik‐cak, branje v obliki spirale in branje v obliki traku. Kot najuspešnejše se izkaže transformacija inverznih frekvenc z branjem v obliki traku, s prebiranjem dvanajstih vrstic. Na naboru 36 sivinskih rastrskih slik različnih ločljivosti dosežemo v povprečju za 26 odstotkov znižanje informacijske entropije.
Keywords: niz, transformacije niza, informacijska entropija, rastrska slika
Published in DKUM: 12.10.2023; Views: 445; Downloads: 50
.pdf Full text (1,08 MB)

9.
Metoda za izboljšanje prostorsko-časovne ločljivosti okoljskih geoprostorskih podatkov z uporabo lokalnih meritev in satelitskih slik : doktorska disertacija
Jernej Cukjati, 2023, doctoral dissertation

Abstract: V doktorski disertaciji predstavimo novo metodo za izboljšavo prostorsko-časovne ločljivosti okoljskih geoprostorskih podatkov. Geoprostorske podatke pogosto dobimo tudi iz meritev, ki jih zajamemo z lokalnimi ali s satelitskimi senzorji. Pomanjkljivost teh zajemov so redki lokalni senzorji in nizka časovna ločljivost satelitskih slik. Prostorsko in časovno ločljivost izboljšamo s souporabo podatkov iz meritev obeh podatkovnih virov. Najprej opazovano območje razdelimo v mrežo pikslov in nad lokalnimi senzorji sestavimo Voronoijev diagram. Središča Voronoijevih celic ustrezajo lokacijam lokalnih senzorjev, ki v danem časovnem trenutku vračajo veljavne izmerjene vrednosti. Za nabor pikslov znotraj vsake posamezne Voronoijeve celice zgradimo ločene regresijske modele s strojnim učenjem. Razlagalne spremenljivke regresijskih modelov so pretekli podatki iz meritev lokalnih senzorjev trenutno izbrane Voronoijeve celice in njenih sosed, ciljne vrednosti pa so iz izbranega nabora pikslov satelitskih slik. Po izračunu vrednosti okoljske spremenljivke v vseh pikslih na opazovanem območju dobimo geolocirano rastrsko sliko okoljske spremenljivke. Predlagano metodo smo uporabili na podatkih meritev lokalnih senzorjev in satelitskih slik toplogrednega plina NO2. Regresijske modele smo zgradili s tremi metodami: algoritmom najbližjih sosedov, linearno regresijo in večplastno naprej usmerjeno nevronsko mrežo. Najvišjo točnost smo dosegli z nevronsko mrežo. Predlagano metodo smo primerjali s petimi referenčnimi metodami, ki so bile predstavljene v zadnjih treh letih. Te metode so: geografsko-časovno obtežena nevronska mreža, prilagodljiva grafovska konvolucijska povratna nevronska mreža, časovna grafovska konvolucijska nevronska mreža z mehanizmom pozornosti, nevronska mreža za izmenjevanje sporočil, združena z mrežami dolgega kratkoročnega spomina, in globoko ansambelsko strojno učenje. Po točnosti je najboljše rezultate dala naša metoda. Najbolj se nam je približala metoda, sestavljena iz nevronske mreže za izmenjavo sporočil in nevronske mreže z dolgim kratkoročnim spominom. Od te smo bili točnejši za približno 5 %.
Keywords: računalništvo, strojno učenje, k-najbližji sosedje, linearna regresija, naprej usmerjena nevronska mreža, daljinsko zaznavanje
Published in DKUM: 02.10.2023; Views: 436; Downloads: 70
.pdf Full text (5,61 MB)

10.
Reflection symmetry detection in earth observation data
David Podgorelec, Luka Lukač, Borut Žalik, 2023, original scientific article

Abstract: The paper presents a new algorithm for reflection symmetry detection, which is specialized to detect maximal symmetric patterns in an Earth observation (EO) dataset. First, we stress the particularities that make symmetry detection in EO data different from detection in other geometric sets. The EO data acquisition cannot provide exact pairs of symmetric elements and, therefore, the approximate symmetry must be addressed, which is accomplished by voxelization. Besides this, the EO data symmetric patterns in the top view usually contain the most useful information for further processing and, thus, it suffices to detect symmetries with vertical symmetry planes. The algorithm first extracts the so-called interesting voxels and then finds symmetric pairs of line segments, separately for each horizontal voxel slice. The results with the same symmetry plane are then merged, first in individual slices and then through all the slices. The detected maximal symmetric patterns represent the so-called partial symmetries, which can be further processed to identify global and local symmetries. LiDAR datasets of six urban and natural attractions in Slovenia of different scales and in different voxel resolutions were analyzed in this paper, demonstrating high detection speed and quality of solutions.
Keywords: computer science, approximate symmetry, partial symmetry, local symmetry, point cloud, voxel, line segment
Published in DKUM: 28.09.2023; Views: 364; Downloads: 13
.pdf Full text (8,92 MB)
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