Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811208
Filip Lauterbach, Patrik Burdiak, J. Rozhon, E. Dervisevic, Martina Slívová, Matej Plakalovic, M. Mehic, M. Voznák
The article presents a series of measurements conducted on the fully-operated Quantum Key Distribution system. These measurements primarily focus on the Quantum Bit Error Rate (QBER), which is the most important parameter of the quantum channel. This parameter was observed and measured for 16 days under the quantum channel’s operating conditions to determine any correlations between the QBER and other quantum link parameters, such as secret key rate. A thorough statistical analysis of the measured data was performed as a part of this investigation and is presented in the paper.
{"title":"Quantum Channel Characteristics from the Point of View of Stability","authors":"Filip Lauterbach, Patrik Burdiak, J. Rozhon, E. Dervisevic, Martina Slívová, Matej Plakalovic, M. Mehic, M. Voznák","doi":"10.1109/ICAT54566.2022.9811208","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811208","url":null,"abstract":"The article presents a series of measurements conducted on the fully-operated Quantum Key Distribution system. These measurements primarily focus on the Quantum Bit Error Rate (QBER), which is the most important parameter of the quantum channel. This parameter was observed and measured for 16 days under the quantum channel’s operating conditions to determine any correlations between the QBER and other quantum link parameters, such as secret key rate. A thorough statistical analysis of the measured data was performed as a part of this investigation and is presented in the paper.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128657553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811236
Ahmed Amine Chafik, J. Gaber, S. Tayane, M. Ennaji
Programmable matter is a system of elements (e.g., smart matters, modular robots, …) that is programmed via user input or autonomous sensing to form a certain shape, by altering its physical characteristics. This paper presents a programmable and reusable device to be used, for example in 4D prototyping and Haptics, using the shapeshifting abilities of smart materials such as shape memory alloys to exhibit a certain behavior controlled by stimulus (heat energy). More precisely, these materials can be programmed and integrated into devices or systems to function according to suitable configurations and conditions (e.g., shape making), via stimuli control as programming means, and wherein the behavior can be modelized using appropriate equations. The programmable device presented in this paper is a shape memory membrane, that makes 3D forms out of a knitted architecture to match a target model, using the shape memory effect. Simulation results using COMSOL are presented and analyzed to model the thermo-mechanical behavior and establish the device’s programming model.
{"title":"Behavioral modeling of knitted shape memory membrane","authors":"Ahmed Amine Chafik, J. Gaber, S. Tayane, M. Ennaji","doi":"10.1109/ICAT54566.2022.9811236","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811236","url":null,"abstract":"Programmable matter is a system of elements (e.g., smart matters, modular robots, …) that is programmed via user input or autonomous sensing to form a certain shape, by altering its physical characteristics. This paper presents a programmable and reusable device to be used, for example in 4D prototyping and Haptics, using the shapeshifting abilities of smart materials such as shape memory alloys to exhibit a certain behavior controlled by stimulus (heat energy). More precisely, these materials can be programmed and integrated into devices or systems to function according to suitable configurations and conditions (e.g., shape making), via stimuli control as programming means, and wherein the behavior can be modelized using appropriate equations. The programmable device presented in this paper is a shape memory membrane, that makes 3D forms out of a knitted architecture to match a target model, using the shape memory effect. Simulation results using COMSOL are presented and analyzed to model the thermo-mechanical behavior and establish the device’s programming model.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131458263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811181
Nedis Dautbašić, A. Mujezinović, I. Turkovic, Maja Muftić Dedović, Ajdin Alihodžić
In this paper approach for the experimental determination of the grounding system impulse impedance under the presence of the high-frequency electromagnetic interference is presented. The considered approach is based on the application of the discrete wavelet transform on the measured signals. Validation of the considered approach has been conducted in several experiments using a vertical grounding electrode. The experimental investigation has been performed using different impulse current peak values and different front rise times. On all measured current and voltage waveforms, high-frequency interferences were registered.
{"title":"Experimental Determination of Grounding System Impulse Impedance under High Frequency Electromagnetic Interferences","authors":"Nedis Dautbašić, A. Mujezinović, I. Turkovic, Maja Muftić Dedović, Ajdin Alihodžić","doi":"10.1109/ICAT54566.2022.9811181","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811181","url":null,"abstract":"In this paper approach for the experimental determination of the grounding system impulse impedance under the presence of the high-frequency electromagnetic interference is presented. The considered approach is based on the application of the discrete wavelet transform on the measured signals. Validation of the considered approach has been conducted in several experiments using a vertical grounding electrode. The experimental investigation has been performed using different impulse current peak values and different front rise times. On all measured current and voltage waveforms, high-frequency interferences were registered.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124303673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811205
Dayana Agudo, Christian Barreto Paredes, Otto Parra Gonzalez, Maria Fernanda Granda
Web 2.0 brought the development of social networks and new elements of interaction that were incorporated into Web sites and devices that supported them. In the field of museums, the emergence of Web 2.0 and Museum 2.0 has made it possible to improve access to information regarding art collections. Due to the COVID-19 pandemic, museums have opted for the introduction of technology permitting virtual access to their collections. However, many applications were developed using traditional development process without considering a methodology dedicated to extended reality applications. This paper describes a methodology for the implementation of extended reality applications to exhibition spaces in museums. Using a quasi-experiment, we evaluate the data collection stage of the proposed methodology to develop an extended reality application to visit exhibition spaces in a museum. Results show that the proposed methodology helps to the software engineers/designers in the development process of extended reality applications.
Web 2.0带来了社交网络的发展和新的交互元素，这些元素被整合到Web站点和支持它们的设备中。在博物馆领域，Web 2.0和Museum 2.0的出现使人们能够更好地获取有关艺术收藏的信息。由于COVID-19大流行，博物馆选择引入允许虚拟访问其藏品的技术。然而，许多应用程序是使用传统的开发过程开发的，没有考虑专用于扩展现实应用程序的方法。本文描述了一种将扩展现实应用于博物馆展览空间的方法。通过准实验，我们评估了所提出方法的数据收集阶段，以开发一个扩展现实应用程序来参观博物馆的展览空间。结果表明，所提出的方法对软件工程师/设计人员在扩展现实应用程序的开发过程中有所帮助。
{"title":"A Methodology to Develop Extended Reality Applications for Exhibition Spaces in Museums","authors":"Dayana Agudo, Christian Barreto Paredes, Otto Parra Gonzalez, Maria Fernanda Granda","doi":"10.1109/ICAT54566.2022.9811205","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811205","url":null,"abstract":"Web 2.0 brought the development of social networks and new elements of interaction that were incorporated into Web sites and devices that supported them. In the field of museums, the emergence of Web 2.0 and Museum 2.0 has made it possible to improve access to information regarding art collections. Due to the COVID-19 pandemic, museums have opted for the introduction of technology permitting virtual access to their collections. However, many applications were developed using traditional development process without considering a methodology dedicated to extended reality applications. This paper describes a methodology for the implementation of extended reality applications to exhibition spaces in museums. Using a quasi-experiment, we evaluate the data collection stage of the proposed methodology to develop an extended reality application to visit exhibition spaces in a museum. Results show that the proposed methodology helps to the software engineers/designers in the development process of extended reality applications.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114662817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811210
Matej Plakalovic, Enio Kaljic, M. Mehic
New generation networks are facing ever greater demands. When testing new network devices that must process packets at extremely high rates, it is essential to test their functionality and desired performance under maximum traffic load. As a result, in order to test the hardware, a traffic generator is required. This paper proposes an affordable and extensible high-speed FPGA-based Ethernet traffic generator. The proposed solution is able of fully utilizing a 40GbE link, with the possibility of manipulating traffic characteristics at the level of an individual packet. Although intended to run on the DE10-Pro system, the proposed design is portable to other FPGA boards with minimal development effort and changes.
{"title":"High-Speed FPGA-Based Ethernet Traffic Generator","authors":"Matej Plakalovic, Enio Kaljic, M. Mehic","doi":"10.1109/ICAT54566.2022.9811210","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811210","url":null,"abstract":"New generation networks are facing ever greater demands. When testing new network devices that must process packets at extremely high rates, it is essential to test their functionality and desired performance under maximum traffic load. As a result, in order to test the hardware, a traffic generator is required. This paper proposes an affordable and extensible high-speed FPGA-based Ethernet traffic generator. The proposed solution is able of fully utilizing a 40GbE link, with the possibility of manipulating traffic characteristics at the level of an individual packet. Although intended to run on the DE10-Pro system, the proposed design is portable to other FPGA boards with minimal development effort and changes.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130862611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811185
Enio Kaljic, A. Maric, Pamela Njemcevic
Flow table lookup is a well-known bottleneck in software-defined network switches. Associative lookup is the fastest but most costly method. On the other hand, an approximate flow classification based on Bloom filters has an outstanding cost-benefit ratio but comes with a downside of false-positive results. Therefore, we propose a new flow table lookup scheme based on Bloom filters and RAM, which offers a good compromise between cost and performance. We solve the problem of false positives of primary Bloom filters by verifying the results and, if necessary, by linearly searching the contents of secondary RAM. Also, we provide a practical implementation in the FPGA-based SDN switch and experimentally show that the proposed solution can achieve better performance than the classic linear search at the low cost typical of Bloom filters.
{"title":"Bloom filter based acceleration scheme for flow table lookup in SDN switches","authors":"Enio Kaljic, A. Maric, Pamela Njemcevic","doi":"10.1109/ICAT54566.2022.9811185","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811185","url":null,"abstract":"Flow table lookup is a well-known bottleneck in software-defined network switches. Associative lookup is the fastest but most costly method. On the other hand, an approximate flow classification based on Bloom filters has an outstanding cost-benefit ratio but comes with a downside of false-positive results. Therefore, we propose a new flow table lookup scheme based on Bloom filters and RAM, which offers a good compromise between cost and performance. We solve the problem of false positives of primary Bloom filters by verifying the results and, if necessary, by linearly searching the contents of secondary RAM. Also, we provide a practical implementation in the FPGA-based SDN switch and experimentally show that the proposed solution can achieve better performance than the classic linear search at the low cost typical of Bloom filters.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125567470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811128
Alvin Huseinović, Yusuf Korkmaz, Halil Bisgin, S. Mrdović, S. Uludag
Various devices and monitoring systems have been developed and deployed in order to monitor the power grid. Indeed, several real-world cyberattacks on power grid systems have been publicly reported. For the transmission and distribution, Phasor Measurement Units (PMUs) constitute the main sensing equipment of the overall wide area monitoring and situational awareness systems by collecting high-resolution data and sending them to Phasor Data Concentrators (PDCs). In this paper, we consider data spoofing attacks against PMU networks. The data between PMUs and PDC(s) are sent through the legacy networks, which are subject to many attack scenarios under with no, or inadequate, countermeasures in protocols, such as IEEE 37.118-2. We consider one potential attack, where an adversary may simply keep injecting a repeated measurement through a compromised PMU to disrupt the monitoring system. This attack is referred to as a Repeated Last Value (RLV) attack. We develop and evaluate countermeasures against RLV attacks using a 2D Convolutional Neural Network (CNN)-based approach, which operates in frames for each second mimicking images, in order to avoid the computational overhead of the classical sample-based classification algorithms, such as SVM. Further, we take this frame-based approach and use it with Support Vector Machine (SVM) for performance evaluation. Our preliminary results show that frame-based CNN as well as SVM provide promising results for RLV attacks while the efficacy of CNN over SVM frame becomes more pronounced as the attack intensity increases.
{"title":"PMU Spoof Detection via Image Classification Methodology against Repeated Value Attacks by using Deep Learning","authors":"Alvin Huseinović, Yusuf Korkmaz, Halil Bisgin, S. Mrdović, S. Uludag","doi":"10.1109/ICAT54566.2022.9811128","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811128","url":null,"abstract":"Various devices and monitoring systems have been developed and deployed in order to monitor the power grid. Indeed, several real-world cyberattacks on power grid systems have been publicly reported. For the transmission and distribution, Phasor Measurement Units (PMUs) constitute the main sensing equipment of the overall wide area monitoring and situational awareness systems by collecting high-resolution data and sending them to Phasor Data Concentrators (PDCs). In this paper, we consider data spoofing attacks against PMU networks. The data between PMUs and PDC(s) are sent through the legacy networks, which are subject to many attack scenarios under with no, or inadequate, countermeasures in protocols, such as IEEE 37.118-2. We consider one potential attack, where an adversary may simply keep injecting a repeated measurement through a compromised PMU to disrupt the monitoring system. This attack is referred to as a Repeated Last Value (RLV) attack. We develop and evaluate countermeasures against RLV attacks using a 2D Convolutional Neural Network (CNN)-based approach, which operates in frames for each second mimicking images, in order to avoid the computational overhead of the classical sample-based classification algorithms, such as SVM. Further, we take this frame-based approach and use it with Support Vector Machine (SVM) for performance evaluation. Our preliminary results show that frame-based CNN as well as SVM provide promising results for RLV attacks while the efficacy of CNN over SVM frame becomes more pronounced as the attack intensity increases.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123069277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811171
E. Turajlić, E. Buza, Amila Akagic
In the fields of computer vision and digital image processing, image segmentation denotes a process whereby an image is segmented into multiple regions. Image segmentation based on multilevel thresholding has received significant attention in recent literature. In this paper, a multilevel thresholding approach based on three different Rao algorithms and Kapur’s entropy is investigated. The performance of the considered thresholding methods is evaluated on a dataset of 10 standard benchmark images using the mean of objective function values, the standard deviation of objective function values, and the best objective function value obtained over a fixed number of independent runs. The experimental results demonstrate the effectiveness of the multilevel thresholding approach based on Rao algorithms and Kapur’s entropy.
{"title":"Multilevel image thresholding based on Rao algorithms and Kapur’s Entropy","authors":"E. Turajlić, E. Buza, Amila Akagic","doi":"10.1109/ICAT54566.2022.9811171","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811171","url":null,"abstract":"In the fields of computer vision and digital image processing, image segmentation denotes a process whereby an image is segmented into multiple regions. Image segmentation based on multilevel thresholding has received significant attention in recent literature. In this paper, a multilevel thresholding approach based on three different Rao algorithms and Kapur’s entropy is investigated. The performance of the considered thresholding methods is evaluated on a dataset of 10 standard benchmark images using the mean of objective function values, the standard deviation of objective function values, and the best objective function value obtained over a fixed number of independent runs. The experimental results demonstrate the effectiveness of the multilevel thresholding approach based on Rao algorithms and Kapur’s entropy.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121137720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811131
Amila Akagic, I. Džafić
The combination of reinforcement learning and deep learning has shown some remarkable results in many scientific fields. Deep reinforcement learning algorithms are particularly good at understanding and modeling adaptive decision-making in dynamic environments. In recent years, this concept has been successfully applied to smart grids. In this paper, we provide a brief introduction to the concepts of reinforcement and deep reinforcement learning to the power system engineers and present research progress and prospects in the field. Additionally, we identify smart grid engineering domains that need extensive pattern-based modeling as being particularly suitable for deep reinforcement learning.
{"title":"Deep Reinforcement Learning in Smart Grid: Progress and Prospects","authors":"Amila Akagic, I. Džafić","doi":"10.1109/ICAT54566.2022.9811131","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811131","url":null,"abstract":"The combination of reinforcement learning and deep learning has shown some remarkable results in many scientific fields. Deep reinforcement learning algorithms are particularly good at understanding and modeling adaptive decision-making in dynamic environments. In recent years, this concept has been successfully applied to smart grids. In this paper, we provide a brief introduction to the concepts of reinforcement and deep reinforcement learning to the power system engineers and present research progress and prospects in the field. Additionally, we identify smart grid engineering domains that need extensive pattern-based modeling as being particularly suitable for deep reinforcement learning.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121060493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811120
Amila Akagic, Senka Krivic, Harun Dizdar, J. Velagić
The scientific discipline of Computer Vision (CV) is a fast developing branch of Machine Learning (ML). It addresses various tasks important for robotics, medicine, autonomous driving, surveillance, security or scene understanding. The development of sensor technologies enabled wide usage of 3D sensors, and therefore, it increased the interest of the CV research community in creating methods for 3D sensor data. This paper outlines seven CV tasks with 3D point cloud data, state-of-the-art techniques, and datasets. Additionally, we identify key challenges.
{"title":"Computer Vision with 3D Point Cloud Data: Methods, Datasets and Challenges","authors":"Amila Akagic, Senka Krivic, Harun Dizdar, J. Velagić","doi":"10.1109/ICAT54566.2022.9811120","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811120","url":null,"abstract":"The scientific discipline of Computer Vision (CV) is a fast developing branch of Machine Learning (ML). It addresses various tasks important for robotics, medicine, autonomous driving, surveillance, security or scene understanding. The development of sensor technologies enabled wide usage of 3D sensors, and therefore, it increased the interest of the CV research community in creating methods for 3D sensor data. This paper outlines seven CV tasks with 3D point cloud data, state-of-the-art techniques, and datasets. Additionally, we identify key challenges.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116167796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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