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1.
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, izvirni znanstveni članek

Opis: 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.
Ključne besede: LIDAR, robot, human-robot collaboration, speed and separation monitoring, intelligent control system, geometric data registration, motion prediction
Objavljeno v DKUM: 16.02.2024; Ogledov: 53; Prenosov: 5
.pdf Celotno besedilo (5,27 MB)
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2.
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: 194; Prenosov: 8
.pdf Celotno besedilo (13,79 MB)
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3.
Vplivi transformacij MTF, IF in RS na informacijsko entropijo rastrskih slik z zveznimi barvnimi toni : diplomsko delo
Rene Vrbnjak Drozg, 2023, diplomsko delo

Opis: 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.
Ključne besede: niz, transformacije niza, informacijska entropija, rastrska slika
Objavljeno v DKUM: 12.10.2023; Ogledov: 315; Prenosov: 34
.pdf Celotno besedilo (1,08 MB)

4.
Metoda za izboljšanje prostorsko-časovne ločljivosti okoljskih geoprostorskih podatkov z uporabo lokalnih meritev in satelitskih slik : doktorska disertacija
Jernej Cukjati, 2023, doktorska disertacija

Opis: 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 %.
Ključne besede: računalništvo, strojno učenje, k-najbližji sosedje, linearna regresija, naprej usmerjena nevronska mreža, daljinsko zaznavanje
Objavljeno v DKUM: 02.10.2023; Ogledov: 288; Prenosov: 47
.pdf Celotno besedilo (5,61 MB)

5.
Reflection symmetry detection in earth observation data
David Podgorelec, Luka Lukač, Borut Žalik, 2023, izvirni znanstveni članek

Opis: 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.
Ključne besede: computer science, approximate symmetry, partial symmetry, local symmetry, point cloud, voxel, line segment
Objavljeno v DKUM: 28.09.2023; Ogledov: 251; Prenosov: 0

6.
IoT and satellite sensor data integration for assessment of environmental variables: a case study on NO2
Jernej Cukjati, Domen Mongus, Krista Rizman Žalik, Borut Žalik, 2022, izvirni znanstveni članek

Opis: This paper introduces a novel approach to increase the spatiotemporal resolution of an arbitrary environmental variable. This is achieved by utilizing machine learning algorithms to construct a satellite-like image at any given time moment, based on the measurements from IoT sensors. The target variables are calculated by an ensemble of regression models. The observed area is gridded, and partitioned into Voronoi cells based on the IoT sensors, whose measurements are available at the considered time. The pixels in each cell have a separate regression model, and take into account the measurements of the central and neighboring IoT sensors. The proposed approach was used to assess NO2 data, which were obtained from the Sentinel-5 Precursor satellite and IoT ground sensors. The approach was tested with three different machine learning algorithms: 1-nearest neighbor, linear regression and a feed-forward neural network. The highest accuracy yield was from the prediction models built with the feed-forward neural network, with an RMSE of 15.49 ×10−6 mol/m2.
Ključne besede: Internet of Things, IoT, remote sensing, sensor integration, machine learning, ensemble method
Objavljeno v DKUM: 22.09.2023; Ogledov: 268; Prenosov: 11
.pdf Celotno besedilo (3,72 MB)
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7.
A framework for multi-objective optimization of virtual tree pruning based on growth simulation
Damjan Strnad, Štefan Kohek, Bedrich Benes, Simon Kolmanič, Borut Žalik, 2020, izvirni znanstveni članek

Opis: We present a framework for multi-objective optimization of fruit tree pruning within a simulated environment, where pruning is performed on a virtual tree model, and its effects on tree growth are observed. The proposed framework uses quantitative measures to express the short-term and long-term effects of pruning, for which potentially conflicting optimization objectives can be defined. The short-term objectives are evaluated on the pruned tree model directly, while the values of long-term objectives are estimated by executing a tree growth simulation. We demonstrate the concept by using a bi-objective case, where the estimated light interceptions of the pruned tree in the current and the next season are used to define separate optimization objectives. We compare the performance of the multi-objective simulated annealing and the NSGA-II method in building the sets of non-dominated pruning solutions. The obtained Pareto front approximations correspond to diverse pruning solutions that balance between optimizing either objective to different extents, which indicates a potential for new applications of the multi-objective pruning optimization concept.
Ključne besede: virtual tree pruning, multi-objective oiptimization, growth simulation, simulated annealing, NSGA-II
Objavljeno v DKUM: 10.07.2023; Ogledov: 251; Prenosov: 29
.pdf Celotno besedilo (1,60 MB)
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8.
Aplikacije računalniških algoritmov
Borut Žalik, 2023

Opis: Učbenik Aplikacije računalniški algoritmov je namenjen študentom prve stopnje študijskega programa računalništvo in informacijske tehnologije s ciljem, spoznati algoritme, ki jih uporabniki pri svojem delu pogosto uporabljajo. Z implementacijo teh algoritmov bodo študentje pri prepotrebno rutino za za vstop v umetnost programiranja univerzalnega stroja, to je računalnika. Učbenik prinaša naslednje vsebine: urejanje podatkov v linearnem času, iskanje vzorcev v nizih, iskanje minimalne razdalje urejanja, preproste šifrirnike, metode brezizgubnega stiskanja podatkov, metode transformacije nizov, priponska polja in priponska drevesa ter algoritme v rastrskem prostoru (verižne kode in krivulje polnjenja prostora).
Ključne besede: urejanje podatkov v linearnem času, iskanje vzorcev v nizih, iskanje minimalne razdalje urejanja, brezizgubno stiskanje podatkov, transformacije nizov, priponska polja in priponska drevesa, verižne kode, krivulje polnjenja prostora
Objavljeno v DKUM: 21.06.2023; Ogledov: 489; Prenosov: 68
.pdf Celotno besedilo (3,01 MB)
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9.
Lossless Compression of High-frequency Intervals in Digital Audio : bachelor's thesis
Ivan Benc, 2022, diplomsko delo

Opis: In this Thesis, an algorithm for lossless audio compression in a time domain is developed and implemented. The algorithm is designed to estimate the signal frequency based on the number of local extremes, and adapts the encoding to the estimated high or low- frequency intervals. As possible adaptations, fitting line segments, quadratic Bézier curves to the signal, and dictionary compression are examined. Residuals are encoded with delta encoding and compressed with binary adaptive sequential coding. The difference in the proportions of line segments and curves used in the high and low-frequency intervals have been detected, but this is not significant enough for this kind of interval discrimination to be meaningful in the current design of the algorithm.
Ključne besede: lossless audio compression, delta encoding, binary adaptive sequential coding, greedy method
Objavljeno v DKUM: 07.11.2022; Ogledov: 481; Prenosov: 37
.pdf Celotno besedilo (1,90 MB)

10.
Primerjava oblakov točk z vgnezdenimi izbočenimi lupinami : diplomsko delo
Matic Pesjak, 2022, diplomsko delo

Opis: V diplomski nalogi najprej opišemo nekatere algoritme, s katerimi primerjamo oblake točk. Zatem podamo lastno zasnovo algoritma za primerjavo, ki temelji na 3D izbočenih lupinah. Predstavimo algoritem hitre izbočene lupine, s pomočjo katerega oblaku točk konstruiramo vgnezdene izbočene lupine. Lastnosti vgnezdenih 3D izbočenih lupin uporabimo v cenilki za razlikovanje med različnimi oblaki točk. Na koncu z eksperimenti demonstriramo prednosti in slabosti metode.
Ključne besede: algoritem, računalniška geometrija, hitra 3D izbočena lupina, cenilka
Objavljeno v DKUM: 24.10.2022; Ogledov: 447; Prenosov: 34
.pdf Celotno besedilo (1,87 MB)

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