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1.
A VAN-Based Multi-Scale Cross-Attention Mechanism for Skin Lesion Segmentation Network
Shuang Liu, Zeng Zhuang, Yanfeng Zheng, Simon Kolmanič, 2023, izvirni znanstveni članek

Opis: With the rise of deep learning technology, the field of medical image segmentation has undergone rapid development. In recent years, convolutional neural networks (CNNs) have brought many achievements and become the consensus in medical image segmentation tasks. Although many neural networks based on U-shaped structures and methods, such as skip connections have achieved excellent results in medical image segmentation tasks, the properties of convolutional operations limit their ability to effectively learn local and global features. To address this problem, the Transformer from the field of natural language processing (NLP) was introduced to the image segmentation field. Various Transformer-based networks have shown significant performance advantages over mainstream neural networks in different visual tasks, demonstrating the huge potential of Transformers in the field of image segmentation. However, Transformers were originally designed for NLP and ignore the multidimensional nature of images. In the process of operation, they may destroy the 2D structure of the image and cannot effectively capture low-level features. Therefore, we propose a new multi-scale cross-attention method called M-VAN Unet, which is designed based on the Visual Attention Network (VAN) and can effectively learn local and global features. We propose two attention mechanisms, namely MSC-Attention and LKA-Cross-Attention, for capturing low-level features and promoting global information interaction. MSC-Attention is designed for multi-scale channel attention, while LKA-Cross-Attention is a cross-attention mechanism based on the large kernel attention (LKA). Extensive experiments show that our method outperforms current mainstream methods in evaluation metrics such as Dice coefficient and Hausdorff 95 coefficient.
Ključne besede: CNNs, deep learning, medical image processing, NLP, semantic segmentation
Objavljeno v DKUM: 14.03.2024; Ogledov: 87; Prenosov: 2
.pdf Celotno besedilo (1,46 MB)
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2.
Literary tourism : the role of Russian 19th century travel literature in the positioning of the smallest European royal capital - Cetinje
Andriela Vitić-Ćetković, Ivona Jovanović, Jasna Potočnik Topler, 2020, izvirni znanstveni članek

Opis: Increasing competition on the global tourism market forces numerous tourist destinations to create a specific image and diversify their offers through innovative and sustainable tourism products. In view of this, there is a range of possibilities for utilizing historical resources, tangible and intangible cultural heritage, including travel literature, which has not been considered in Montenegro thus far in the context of potentials for enhancing the tourist offer. This paper is focusing on the research of travel literature by 19th century authors from Russia who wrote about Cetinje and Montenegro, as well as the possibilities of creating a destination image and diversified experience for specific market niches, primarily the tourists from Russia who have been among the most numerous in Montenegro. The expected outcome of the research is to point out the importance of valorisation of Russian traveler literature in the context of creating a destination image. Considering the negative propaganda of a part of the media in Russia when Montenegro entered NATO in 2017, it is expected that this Balkan and Adriatic country, whose primary business is tourism, will have to identify and acquire state-of-the-art modalities for attracting new target segments from the Russian Federation. In this paper, literary tourism with the concepts of town - museum, town of books and storytelling, as marketing communications tools, are proposed to promote the revival and valorization of historical events, historical figures and Cetinje's former image in the positioning of the tourism destination, also in the conte xt of sustainable tourism development.
Ključne besede: travel literature, literary tourism, heritage, destination image, destination positioning, storytelling, Monte Negro, Cetinje
Objavljeno v DKUM: 26.01.2024; Ogledov: 120; Prenosov: 2
.pdf Celotno besedilo (2,75 MB)
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3.
The influence of façade colour, glazing area and geometric configuration of urban canyon on the spectral characteristics of daylight
Nataša Šprah, Jaka Potočnik, Mitja Košir, 2024, izvirni znanstveni članek

Opis: Since the non-image-forming (NIF) effect of daylight on the human circadian system is widely accepted, adequate exposure to daylight is now considered one of the elements of a healthy life. In urban environment, one of the prerequisites for adequately lit indoor spaces is the amount and quality of daylight reaching the window, which is highly dependent on the characteristics of the urban environment. The aim of the study was to determine whether there are correlations between urban density (i.e., distance between buildings, building height), façade surface characteristics (i.e., colour and Window-to-Wall Ratios – WWR) and NIF potential of daylight. The study was conducted on a parametric geometric model of a street canyon covering a wide range of characteristics. Simulation results were interpreted using the Relative Melanopic Efficacy coefficient and Sky View Factor. The results indicate that the colour of the opposite façade can substantially impact the resulting NIF potential, especially for orange-red or blue hues. The results of the study show that this influence for building heights between 3 and 8 storeys becomes significant when the width of the urban canyon is less than 25 m and becomes substantially smaller at WWRs above 30 %.
Ključne besede: urban planning, daylight, non-image forming effects of light, circadian light, urban canyon, façade colour
Objavljeno v DKUM: 19.01.2024; Ogledov: 216; Prenosov: 12
.pdf Celotno besedilo (14,66 MB)
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4.
High strain-rate deformation analysis of open-cell aluminium foam
Anja Mauko, Mustafa Sarıkaya, Mustafa Güden, Isabel Duarte, Matej Borovinšek, Matej Vesenjak, Zoran Ren, 2023, izvirni znanstveni članek

Opis: This study investigated the high-strain rate mechanical properties of open-cell aluminium foam M-pore®. While previous research has examined the response of this type of foam under quasi-static and transitional dynamic loading conditions, there is a lack of knowledge about its behaviour under higher strain rates (transitional and shock loading regimes). To address this gap in understanding, cylindrical open-cell foam specimens were tested using a modified Direct Impact Hopkinson Bar (DIHB) apparatus over a wide range of strain rates, up to 93 m/s. The results showed a strong dependency of the foam's behaviour on the loading rate, with increased plateau stress and changes in deformation front formation and propagation at higher strain rates. The internal structure of the specimens was examined using X-ray micro-computed tomography (mCT). The mCT images were used to build simplified 3D numerical models of analysed aluminium foam specimens that were used in computational simulations of their behaviour under all experimentally tested loading regimes using LS-DYNA software. The overall agreement between the experimental and computational results was good enough to validate the built numerical models capable of correctly simulating the mechanical response of analysed aluminium foam at different loading rates.
Ključne besede: Open-cell aluminium foam, Micro-computed tomography, High-strain rate, Direct impact hopkinson bar, Digital image correlation, Computer simulation
Objavljeno v DKUM: 06.12.2023; Ogledov: 306; Prenosov: 28
.pdf Celotno besedilo (3,28 MB)
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5.
Design of an Embedded Position Sensor with Sub-mm Accuracy : magistrsko delo
Matej Nogić, 2019, magistrsko delo

Opis: This master’s thesis presents the development of a machine-vision based localization unit developed at Robert Bosch GmbH, Corporate Sector Research and Advance Engineering in Renningen, Germany. The localization unit was developed primarily for position detection purposes with three degrees of freedom in highly versatile manufacturing systems but has an immense potential to be used anywhere where a precise, low-cost localization method on a two-dimensional surface is required. The complete product development cycle was carried out, from the components selection, schematic and optical system design, to the development of machine vision algorithms, four-layer Printed Circuit Board design and evaluation using an industrial robot. Thanks to the use of a patented two-dimensional code pattern, the localization unit can cover a surface area of 49 km2. The size and speed optimized, self-developed machine-vision algorithms running on a Cortex-M7 microcontroller allow achieving an accuracy of 100 µm and 60 Hz refresh rate.
Ključne besede: localization, machine-vision, code pattern, image sensor, embedded system
Objavljeno v DKUM: 14.01.2020; Ogledov: 1109; Prenosov: 44
.pdf Celotno besedilo (18,20 MB)

6.
Vergleich des Images der deutschen Sprache im dritten Bildungsabschnitt an zwei verschiedenen Grundschulen in Prekmurje
Matija Toth, 2019, diplomsko delo

Opis: Im Mittelpunkt der Diplomarbeit mit dem Titel ‚‚Vergleich des Images der deutschen Sprache im dritten Bildungsabschnitt an zwei verschiedenen Grundschulen in Prekmurje‘‘ steht das Image der deutschen Sprache bzw. ihr Vergleich an zwei, von Hinsicht des mehrsprachigen Unterrichtes, abgrenzenden Grundschulen in Slowenien. Das Ziel der Untersuchung ist der Vergleich des Images der deutschen Sprache zwischen zwei Befragungsgruppen, die jeweils Schüler der einsprachigen Grundschule in Murska Sobota oder der zweisprachigen Grundschule in Lendava sind und sich im Alter zwischen zwölf und fünfzehn Jahren befinden. Die Forschung fokussiert sich auf die eventuellen Unterschiede zwischen den Sprachimages der zwei untersuchten Gruppen. Im theoretischen Teil wird definiert, was eigentlich unter dem Begriff Image verstanden wird, von welchen Faktoren das Image einer Sprache beeinflusst wird, was die verbreitetsten Mythen über Sprachen sind und welche Rolle die englische Sprache dabei spielt. Im empirischen Teil wird eine Analyse des Fragebogens folgen, das dieses Thema behandelt. An der Umfrage nahmen 149 Schüler des dritten Bildungsabschnittes aus Lendava und 139 aus Murska Sobota teil. Insgesamt wurde der Fragebogen von 278 Schülern ausgefüllt. Der Fragebogen beinhaltet Aufgabenstellungen und Fragen, mit Hilfe dessen man sich ein Bild über das Image des Deutschen, bei den Schülern der jeweiligen Schulen, machen konnte. Von großer Bedeutung war es, die subjektiven Informationen der Individuen zu bekommen, um so zu einem authentischen Resultat der wissenschaftlichen Arbeit zu kommen.
Ključne besede: Image der deutschen Sprache, mehrsprachiger Unterricht, Vergleich zweier Schulen
Objavljeno v DKUM: 16.10.2019; Ogledov: 1155; Prenosov: 186
.pdf Celotno besedilo (1,21 MB)

7.
Estimating the size of plants by using two parallel views
Barbara Videc, Jurij Rakun, 2017, izvirni znanstveni članek

Opis: This paper presents a method of estimating the size of plants by using two parallel views of the scene, taken by a common digital camera. The approach relays on the principle of similar triangles with the following constraints: the resolution of the camera is known; the object is always in parallel to the camera sensor and the intermediate distance between the two concessive images is available. The approach was first calibrated and tested using one artificial object in a controlled environment. After that real examples were taken from agriculture, where we measured the distance and the size of a vine plant, apple and pear tree. By comparing the calculated values to measured values, we concluded that the average absolute error in distance was 0.11 m or around 3.7 %, and the absolute error in high was 0.09 m or 4.6 %.
Ključne besede: digital image processing, size, digital camera, pixels, similar triangles
Objavljeno v DKUM: 10.10.2018; Ogledov: 1190; Prenosov: 303
.pdf Celotno besedilo (727,92 KB)
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8.
Determining the grain size distribution of granular soils using image analysis
Nihat Dipova, 2017, izvirni znanstveni članek

Opis: Image-processing technology includes storing the images of objects in a computer and processing them with the computer for a specified purpose. Image analysis is the numerical expression of the images of objects by means of mimicking the functioning of the human visual system and the generation of numerical data for calculations that will be made later. Digital image analysis provides the capability for rapid measurement, which can be made in near-real time, for numerous engineering parameters of materials. Recently, image analysis has been used in geotechnical engineering practices. Grain size distribution and grain shape are the most fundamental properties used to interpret the origin and behaviour of soils. Mechanical sieving has some limitations, e.g., it does not measure the axial dimension of a particle, particle shape is not taken into consideration, and especially for elongated and flat particles a sieve analysis will not yield a reliable measure. In this study the grain size distribution of sands has been determined following image-analysis techniques, using simple apparatus, non-professional cameras and open-code software. The sample is put on a transparent plate that is illuminated with a white backlight. The digital images were acquired with a CCD DSLR camera. The segmentation of the particles is achieved by image thresholding, binary coding and particle labeling. The geometrical measurements of each particle are obtained using an automated pixel-counting technique. Local contacts or limited overlaps were overcome using a watershed split. The same sample was tested by traditional sieve analysis. An image-analysis-based grain size distribution has been compared with a sieve-analysis distribution. The results show that the grain size distribution of the image-based analysis and the sieve analysis are in good agreement.
Ključne besede: image analysis, image processing, grain size, sand
Objavljeno v DKUM: 18.06.2018; Ogledov: 1324; Prenosov: 147
.pdf Celotno besedilo (1,27 MB)
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9.
An overview of image analysis algorithms for license plate recognition
Khalid Aboura, Rami Al-Hmouz, 2017, izvirni znanstveni članek

Opis: Background and purpose: We explore the problem of License Plate Recognition (LPR) to highlight a number of algorithms that can be used in image analysis problems. In management support systems using image object recognition, the intelligence resides in the statistical algorithms that can be used in various LPR steps. We describe a number of solutions, from the initial thresholding step to localization and recognition of image elements. The objective of this paper is to present a number of probabilistic approaches in LPR steps, then combine these approaches together in one system. Most LPR approaches used deterministic models that are sensitive to many uncontrolled issues like illumination, distance of vehicles from camera, processing noise etc. The essence of our approaches resides in the statistical algorithms that can accurately localize and recognize license plate. Design/Methodology/Approach: We introduce simple and inexpensive methods to solve relatively important problems, using probabilistic approaches. In these approaches, we describe a number of statistical solutions, from the initial thresholding step to localization and recognition of image elements. In the localization step, we use frequency plate signals from the images which we analyze through the Discrete Fourier Transform. Also, a probabilistic model is adopted in the recognition of plate characters. Finally, we show how to combine results from bilingual license plates like Saudi Arabia plates. Results: The algorithms provide the effectiveness for an ever-prevalent form of vehicles, building and properties management. The result shows the advantage of using the probabilistic approached in all LPR steps. The averaged classification rates when using local dataset reached 79.13%. Conclusion: An improvement of recognition rate can be achieved when there are two source of information especially of license plates that have two independent texts.
Ključne besede: image analysis, probabilistic modeling, signal processing, license plate recognition
Objavljeno v DKUM: 28.11.2017; Ogledov: 1296; Prenosov: 348
.pdf Celotno besedilo (1,01 MB)
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10.
The accuracy of the germination rate of seeds based on image processing and artificial neural networks
Uroš Škrubej, Črtomir Rozman, Denis Stajnko, 2015, izvirni znanstveni članek

Opis: This paper describes a computer vision system based on image processing and machine learning techniques which was implemented for automatic assessment of the tomato seed germination rate. The entire system was built using open source applications Image J, Weka and their public Java classes and linked by our specially developed code. After object detection, we applied artificial neural networks (ANN), which was able to correctly classify 95.44% of germinated seeds of tomato (Solanum lycopersicum L.).
Ključne besede: image processing, artificial neural networks, seeds, tomato
Objavljeno v DKUM: 14.11.2017; Ogledov: 1449; Prenosov: 444
.pdf Celotno besedilo (353,43 KB)
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