Niko Lukac

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Verified

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• PhD
• Associate Professor at University of Maribor

In this paper, a novel method for estimating high-resolution isotropic broadband albedo is proposed, by downscaling satellite-derived albedo using an optimization approach. At first, broadband albedo is calculated from the lower-resolution multispectral satellite image using standard narrow-to-broadband (NTB) conversion, where the surfaces are cons...

Maximizing the energy output of photovoltaic (PV) systems is becoming increasingly important. Consequently, numerous approaches have been developed over the past few years that utilize remote sensing data to predict or map solar potential. However, they primarily address hypothetical scenarios, and few focus on improving existing installations. Thi...

In the past years various methods have been developed to estimate high-resolution solar potential in urban areas, by simulating solar irradiance over surface models that originate from remote sensing data. In general, this requires discretisation of solar irradiance models that estimate direct, reflective, and diffuse irradiances. The latter is mos...

Multispectral satellite imagery offers a new perspective for spatial modelling, change detection and land cover classification. The increased demand for accurate classification of geographically diverse regions led to advances in object-based methods. A novel spatiotemporal method is presented for object-based land cover classification of satellite...

Computer resources and programming solutions have always been utilised with the aim of improving efficiency; consequently, many optimisations have been developed in the past. This chapter first considers some typical characteristic optimisations in computing. Following this, a string transformation technique, Move with Interleaving (MwI), is explai...

This paper investigates the economic feasibility of utilising energy flexibility in aluminium production as a viable solution to leverage electricity surpluses arising from the increasing number of photovoltaic (PV) system installations. Future trends suggest that the generation capacity of PV systems will soon surpass consumption, leading to signi...

Processing measurement data is fundamental in the field of high-tech instrumentation, where precision, collection, analysis, and visualization of data are of great importance. Extensive amounts of data ought to be displayed and processed to ensure smooth user experience. Tabular displays are therefore common, being more comprehensible for the avera...

The increase in unstructured textual data has created a pressing demand for effective information extraction techniques. This paper explores the integration of Named Entity Extraction (NEE) using deep learning within the Neo4j graph database. Utilizing the Rebel Large Model, we converted raw text into structured knowledge graphs. The primary object...

Various implementations of the Move with Interleaving transform are discussed in this paper, with the transformation itself explained briefly at first. The transform has an expected time complexity of O(n), where n represents the length of the sequence being transformed. The importance of implementation also grows as the sequences become longer. Th...

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 tha...

In the ever-evolving landscape of data visualization and extraction, deep learning techniques have become increasingly pivotal. Addressing this, our paper conducts a sensitivity analysis of Named Entity Extraction on text related to the infamous Panama Papers. We combine the Rebel and Natural Language Processing models to extract entities and relat...

Automated decision tools, such as advanced energy management systems, are required to involve the electrical grid users in energy flexibility services. This paper focuses on the prediction models as a substantial part of decision strategy in advanced energy management systems and on advanced energy management systems as a tool that supports the act...

The characterisation of geometric shapes produces their concise description and is, therefore, important for subsequent analyses, for example in Computer Vision, Machine Learning, or shape matching. A new method for extracting characterisation vectors of 2D geometric shapes is proposed in this paper. The shape of interest, embedded into a raster sp...

A new approach is proposed for lossless raster image compression employing interpolative coding. A new multifunction prediction scheme is presented first. Then, interpolative coding, which has not been applied frequently for image compression, is explained briefly. Its simplification is introduced in regard to the original approach. It is determine...

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 prepro...

Datasets often lack diversity to train robust classification models, capable of being used in real-life scenarios. Neural network-based generative models learn characteristics to generate synthetic (i.e. augmented) data, with the goal of increasing the diversity in datasets. A comparison is presented between Beta-VAE and WGAN-GP as ResNet-18 based...

Datasets often lack diversity to train robust classification models, capable of being used in real-life scenarios. Neural network-based generative models learn characteristics to generate synthetic (i.e. augmented) data, with the goal of increasing the diversity in datasets. A comparison is presented between Beta-VAE and WGAN-GP as ResNet-18 based...

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 ba...

Acts of fraud have become much more prevalent in the financial industry with the rise of technology and the continued economic growth in modern society. Fraudsters are evolving their approaches continuously to exploit the vulnerabilities of the current prevention measures in place, many of whom are targeting the financial sector. To overcome and in...

Entity alignment refers to the process of discovering entities representing the same object in different knowledge graphs (KG). Recently, some studies have learned other information about entities, but they are aspect-level simple information associations, and thus only rough entity representations can be obtained, and the advantage of multi-facete...

Reliable forest growth forecasting requires detailed tree data for forest simulation, while manual on-site collection of relevant data is work-intensive and unfeasible in larger forests. This paper proposes a complete methodology for fully automated forest growth simulation that relies primarily on airborne topographic Light Detection And Ranging (...

A new algorithm is presented for detecting the global reflection symmetry of geometric objects. The algorithm works for 2D and 3D objects which may be open or closed and may or may not contain holes. The algorithm accepts a point cloud obtained by sampling the object’s surface at the input. The points are inserted into a uniform grid and so-called...

V članku predstavimo postopke obdelave velikih količin nestrukturiranih geometrijskih podatkov, pridobljenih s prebirniki LiDAR. Najprej opišemo postopke klasifikacije točk LiDAR v točke, ki ležijo na Zemljinem površju. Opravimo kratek pregled obstoječih metod nato pa na kratko predstavimo našo metodo, temelječo na konceptih matematične morfologije...

This work introduces a new region merging algorithm operating in raster space represented by a 4-connected graph. Necessary definitions are introduced first to derive a new merging function formally. An implementation is described after that, which consists of two steps: a determination of the shared trails of the input cycles, and construction of...

Trees are natural objects, where deviations through the branches amplify geometric data for 3D representation and bring challenges to various applications dealing with 3D models, such as compression, visualization, symmetry detection, and radiative transfer simulation. This data article describes dataset of approximately symmetric 3D tree models wi...

This paper introduces a new integrated framework for short-term time series forecasting used as decision logic support in Energy Management Systems (EMS). The proposed framework defines data preprocessing, forecast model training, and adaptation techniques. For data preprocessing, Gaussian and Kalman filtering were used in offline learning on histo...

The Liao Dynasty was a minority regime established by the Khitan on the grasslands of northern China. To promote and spread the cultural knowledge of the Liao Dynasty, an intelligent question-and-answer system is constructed based on the knowledge graph in the historical and cultural field of the Liao Dynasty. In the traditional question answering...

This paper aims to automatically reconstruct 3D building models on a large scale using a new approach on the basis of half-spaces, while making no assumptions about the building layout and keeping the number of input parameters to a minimum. The proposed algorithm is performed in two stages. First, the airborne LiDAR data and buildings’ outlines ar...

Question-answering systems based on knowledge graphs are extremely challenging tasks in the field of natural language processing. Most of the existing Chinese Knowledge Base Question Answering(KBQA) can only return the knowledge stored in the knowledge base by extractive methods. Nevertheless, this processing does not conform to the reading habits...

A new method for encoding a sequence of integers, named Binary Adaptive Sequential Coding with Return to Bias, is proposed in this paper. It extends the compressing pipeline for chain codes’ compression consisting of Burrows Wheeler Transform, Move-To-Front Transform, and Adaptive Arithmetic Coding. We also explain when to include the Zero-Run Tran...

When it comes to the proliferation of photovoltaic (PV) systems, technological solutions have to go hand in hand with optimized policy approaches and regulatory frameworks. This paper proposes a new application of state-of-the-art PV potential estimation method based on Light Detection And Ranging (LiDAR) data targeted toward individual household s...

Increasing population and urbanisation threaten sustainable urban development due to increased resource consumption and emissions. As buildings are one of the largest energy consumers, it is crucial that their thermal load can be inspected on a large scale and at the highest resolution possible. The proposed method is performed in two stages. First...

Burrows-Wheeler Transform, followed by Move-To-Front Transform, are often used transformation techniques in data compression. They may reduce the information entropy of the input sequence, which becomes more compressible in this way. This paper suggests an alternative, a Prediction-based Move-To-Front Transform, which may replace the aforementioned...

The availability of high-resolution LiDAR (Light Detection And Ranging) geospatial data has increased immensely, providing new opportunities to solve challenges in the field of spatial energy planning. This paper presents a new method for large-scale placement of photovoltaic arrays over buildings' rooftops in an optimal manner by using the global...

A lossless chain code compression algorithm consisting of Burrows-Wheeler Transform, Move-To-Front Transform, and a modified interpolative coding is presented in this paper. The interpolative coding divides a strictly increasing array of integers and encodes the middle element recursively, where the required number of bits is obtained from the diff...

Presented paper addresses the problem of proper large-scale integration of photovoltaic (PV) systems in urban area distribution network (DN). A methodology for minimization of annual energy losses in DN by optimal placement of PV systems, which simultaneously considers rooftop PV potential and time dependent network operation, is presented. Optimal...

This paper proposes a novel visualization and analytics tool, which is capable of searching for hidden relationships and patterns within large multi-dimensional data. The goal of the presented tool is to represent the data in novel ways, understandable and useful to the data owner, with new visual and statistical analytics. Various statistics are o...

In the last decades, the established Airborne Laser Scanning (ALS) approach for urban tree species classification has been increasingly complemented by laser scanning datasets measured from further platforms such as Terrestrial Laser Scanning (TLS), Mobile Laser Scanning (MLS), and UAV-borne Laser Scanning (ULS). However, the characteristics of the...

This paper considers the use of interpolative coding for lossless chain code compression. The most popular chain codes are used, including Freeman chain code in eight (F8) and four directions (F4), Vertex Chain Code (VCC), and three-orthogonal chain code (3OT). The whole compression pipeline consists of the Burrows–Wheeler transform, Move-To-Front...

With the growing urbanization and environmental concerns over buildings' energy consumption and carbon footprint, the demand for energy-efficient building design is greater than ever. This paper addresses these concerns by presenting a novel method for estimating and optimising the thermal load (i.e. total energy load for heating and cooling) of a...

This paper introduces a new algorithm for Boolean operations on rasterized geometric shapes that are represented with chain codes. The algorithm works in three steps. Firstly, the chain code symbols are transformed in the Hilbert space, where the overlaid chain code symbols are recognised. After that, a suitable starting cell is determined. Finally...

Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms...

The increasing availability of airborne Light Detection And Ranging (LiDAR) data provides new opportunities for environmental simulations. This paper proposes a new method for wind resource assessment by using wind simulation over 3D geometry extracted from classified LiDAR data. The simulation of wind flow is performed by using Smoothed Particle H...

This paper presents the analysis of the impact of dispersed source production on the electric distribution network. The focus is on the production of electric energy by photovoltaic systems in public distribution networks. Photovoltaic systems may in certain cases influence voltage quality in public distribution networks, which is determined by the...

This paper deals with a method for determining the rating of roofs’ segments in urban areas regarding their suitability for the installation of different photovoltaic (PV) systems. In order to determine the received irradiance of individual roofs, their geometry is described based on LiDAR (Light Detection And Ranging) data, in order to estimate ac...

This paper proposes a parallelized online optimization of low voltage distribution network (LVDN) operation. It is performed on a Graphics Processing Unit (GPU) by combining the optimization procedure with the load flow method. In the case study, performed for the test LVDN with distributed generators (DGs) and controllable loads, differential evol...

Within the last few years, the increase of the world's energy consumption has substantially impacted the environment. Solar energy initiative is more than ever involved to tackle this issue, especially when deploying PV (photovoltaic) systems over large-scale residential areas. However, not all surfaces in these areas are economically suitable, whi...

Kljub obstoju različnih tujih računalniških programov, ki omogočajo fotogrametrični zajem podatkov iz aerofotografij velikega formata, tudi slovenska stroka zadnjih dvajset let ne zaostaja za tujino in izdeluje svoje fotogrametrične programe. Ti omogočajo večjo optimizacijo 3D-zajema pri slovenskih projektih: na primer pohitritev zajema zaradi vnap...

This paper considers the suitability of string transformation techniques for lossless chain codes' compression. The more popular chain codes are compressed including the Freeman chain code in four and eight directions, the vertex chain code, the three orthogonal chain code, and the normalised directional chain code. A testing environment consisting...

Proliferation of distributed generation units, integrated within the distribution network requires increased attention to their proper placements. In urban areas, buildings' rooftops are expected to have greater involvement in the deployment of PV (photovoltaic) systems. This paper proposes a novel procedure for determining roof surfaces suitable f...

The paper evaluates the energy savings in a low-voltage power distribution network by optimising the photovoltaic-system (PVS) reactive-power generation. The evaluation is made on a model of a real low-voltage power distribution network with two 50 kWp PVSs installed. The time frame of energy-savings evaluation is one year. The PVS active power is...

With the higher penetration of the distributed power generation units in the power distribution network it is important to evaluate their impact on the power network operating conditions. The paper analyzes the impact of the active- And reactive-power generation of additional photovoltaic (PV) units to be installed in a part of the medium-voltage n...

Aerial laser scanning of the whole territory of Slovenia was performed with first return point densities of 2-5 points/m 2 in years 2014 and 2015. The data were processed with Slovenian gLidar software, enabling quick product line and resulting in the following products: classified point cloud, ground point cloud, digital terrain model (DTM) with g...

As the data acquisition capabilities of Earth observation (EO) satellites have been improved substantially in the past few years, large amount of high-resolution satellite images are downlinked continuously to ground stations. Such amount of data increases rapidly beyond the users' capability to access the images' content in reasonable time. Hence,...

The search for solar buildings is one of the primary challenges in urban planning, especially when developing self-sustainable cities. This work uses an evolutionary approach for finding the optimal building model based on airborne Light Detection And Ranging (LiDAR) laser-scanned data, regarding solar potential. The method considers self-adaptive...

This paper deals with the evaluation of electrical energy savings in a low voltage distribution network, gathered by reduced energy losses. The latter is achieved by optimal reactive power generation of photovoltaic (PV) systems, where losses in the low voltage network and distribution transformer are taken into consideration. The energy savings ar...

This paper introduces a new approach for lossless chain code compression. Firstly, the chain codes are converted into the binary stream, independent on the input chain code. Then, the compression is done using three modes: RLE^0, LZ77^0 and COPY. RLE^0 compresses the runs of the 0-bits, LZ77^0 is a simplified version of LZ77 and handles the repetit...

Direct point-based rendering is a popular method in scientific visualization, since the number of point-based datasets increased dramatically in the past few years. At the same time, rendering of point primitives is becoming less efficient as the data size increases. Point splatting, volume-based rendering, or isosurface extraction are well-known a...

This paper presents a GPU-based method for denoising of time series images obtained by confocal microscopy, in order to study the oscillations of calcium and membrane voltage potential in beta cells. Since denoising of captured images is one of the first crucial steps, it is desirable that it is highly efficient and fast. This is especially importa...

Clustering is one of the better known unsupervised learning methods with the aim of discovering structures in the data. This paper presents a distance-based Sweep-Hyperplane Clustering Algorithm (SHCA), which uses sweep-hyperplanes to quickly locate each point's approximate nearest neighbourhood. Furthermore, a new distance-based dynamic model that...

Modern remote sensing technologies such as airborne Light Detection And Ranging (LiDAR) laser scanning enables the acquisition of large unstructured point cloud datasets representing highly detailed surfaces. Various methods have been developed to fuse LiDAR data with optical imagery in order to enrich the points with color information. However, op...

One of the major challenges in the topographic mapping and fast generation of digital terrain or surface models from stereo optical aerial or satellite imagery is the stereo rectification preprocessing step. The general case is the use of extrinsic and intrinsic parameters from each calibrated camera, in order to establish epipolar geometry. Stereo...

Over recent years, photovoltaic systems have become increasingly popular for the installation on buildings’ rooftops. One of the main questions for investors is to find which rooftop is suitable for photovoltaic system installation in order produce maximum electrical energy. This paper presents Geographic Information System (GIS) for the solar and...

One of the major challenges today is assessing the suitability of PV (photovoltaic) systems' installations on buildings' roofs regarding the received solar irradiance. The availability of aerial laser-scanning, namely LiDAR (Light Detection And Ranging), means that assessment can be performed automatically over large-scale urban areas in high accur...

Chain codes are the most size-efficient representations of rasterised binary shapes and contours. This paper considers a new lossless chain code compression method based on move-to-front transform and an adaptive run-length encoding. The former reduces the information entropy of the chain code, whilst the latter compresses the entropy-reduced chain...

This paper proposes a new framework for ground extraction and building detection in LiDAR data. The proposed approach constructs the connectivity of a grid over the LiDAR point-cloud in order to perform multi-scale data decomposition. This is realised by forming a top-hat scale-space using differential morphological profiles (DMPs) on points’ resid...

The k-nearest neighbours (k-NN) search is one of the most critical non- parametric methods used in data retrieval and similarity tasks. Over recent years fast k-NN processing for large amount of high-dimensional data is increasingly demanded. Locality-sensitive hashing is a viable solution for computing fast ap- proximate nearest neighbours (ANN) w...

This paper considers a new method for building-extraction from LiDAR data. This method uses multi-scale levelling schema or MSLS-segmentation based on differential morphological profiles for removing non-building points from LiDAR data during the data denoising step. A new morphological algorithm is proposed for the detection of flat regions and ob...

Solar potential estimation using LiDAR data is an efficient approach for finding suitable roofs for photovoltaic systems' installations. As the amount of LiDAR data increases, the non-parallel methods take considerable time to accurately estimate the solar potential. Although supercomputing provides a possible solution, it is still too expensive an...

The roof surfaces within urban areas are constantly attracting interest regarding the installation of photovoltaic systems. These systems can improve self-sufficiency of electricity supply, and can help to decrease the emissions of greenhouse gases throughout urban areas. Unfortunately, some roof surfaces are unsuitable for installing photovoltaic...

Large quantities of simulated cosmological particle-based data cause considerable problems when it comes to real-time visualization. This paper considers an out-of-core approach for solving visualization problems on a single-desktop workstation. The approach proposed in this paper consists of two phases: the data preprocessing and its visualization...

This paper presents an efficient approach for visualizing large quantities of cosmological particle data. The data is represented as 3D points and originates from various sources. Due to the size of the cosmos, huge amounts of observed and simulated data can cause considerable problems for real-time visualization. Our approach consists of preproces...