Pub Date : 2023-05-23DOI: 10.1109/SACI58269.2023.10158669
Silvana Qose, Rajnai Zoltán, Beatrix Fregan
Blockchain technology upends the status quo by providing a productive and decentralized platform for data management. Blockchain is a data management system that has the potential to enable accountability and transparency. Every computer network user may have a duplicate copy of the Blockchain, a ledger of transactions where network members validate data submitted into the ledger; once entered, the data cannot be changed [1], [2]. Revenue cycle administration, doctor credentialing, electronic health records, and supply chain administration are applications in the healthcare industry, yet, their widespread adoption is threatened by prospective government regulation and internal concerns [3].Additionally, the fact that the data in the Blockchain is duplicated across all of the network’s nodes fosters openness and transparency, enabling healthcare stakeholders, particularly the patients, to understand how, by whom, when, and how their data is utilized [4]. More crucially, since the data in the ledger is duplicated throughout several nodes in the network has no impact on the ledger’s current state. As a result, Blockchain, by its very nature, can defend against possible data loss, corruption, and security threats like ransomware assault [5].
{"title":"Blockchain Technology in Healthcare Industry: Benefits and Issues","authors":"Silvana Qose, Rajnai Zoltán, Beatrix Fregan","doi":"10.1109/SACI58269.2023.10158669","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158669","url":null,"abstract":"Blockchain technology upends the status quo by providing a productive and decentralized platform for data management. Blockchain is a data management system that has the potential to enable accountability and transparency. Every computer network user may have a duplicate copy of the Blockchain, a ledger of transactions where network members validate data submitted into the ledger; once entered, the data cannot be changed [1], [2]. Revenue cycle administration, doctor credentialing, electronic health records, and supply chain administration are applications in the healthcare industry, yet, their widespread adoption is threatened by prospective government regulation and internal concerns [3].Additionally, the fact that the data in the Blockchain is duplicated across all of the network’s nodes fosters openness and transparency, enabling healthcare stakeholders, particularly the patients, to understand how, by whom, when, and how their data is utilized [4]. More crucially, since the data in the ledger is duplicated throughout several nodes in the network has no impact on the ledger’s current state. As a result, Blockchain, by its very nature, can defend against possible data loss, corruption, and security threats like ransomware assault [5].","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127036140","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158548
Ágnes Csiszárik-Kocsir, J. Varga
In the competitive economy of the 21st century, innovation and the attitude to innovation are key factors. The depletion of traditional natural resources in today’s fast-changing world has virtually eliminated the former engine of economic growth, and a new approach is needed to enable economic actors to cope with the new environment. New solutions are the only way to overcome the anomaly of natural resources. It is essential that all economic actors, from micro to large enterprises, can play their part in this process. It is therefore of the utmost importance that the conditions are created in the near future to promote and stimulate innovation. The aim of this study is to present the Hungarian SME sector’s view on the factors that stimulate innovation, assessing the potential characteristics that can contribute to these processes and behaviours.
{"title":"Innovation and factors leading to innovative behaviour according to Hungarian businesses1","authors":"Ágnes Csiszárik-Kocsir, J. Varga","doi":"10.1109/SACI58269.2023.10158548","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158548","url":null,"abstract":"In the competitive economy of the 21st century, innovation and the attitude to innovation are key factors. The depletion of traditional natural resources in today’s fast-changing world has virtually eliminated the former engine of economic growth, and a new approach is needed to enable economic actors to cope with the new environment. New solutions are the only way to overcome the anomaly of natural resources. It is essential that all economic actors, from micro to large enterprises, can play their part in this process. It is therefore of the utmost importance that the conditions are created in the near future to promote and stimulate innovation. The aim of this study is to present the Hungarian SME sector’s view on the factors that stimulate innovation, assessing the potential characteristics that can contribute to these processes and behaviours.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"436 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132523840","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158568
Anett Popovics, Mónika Garai-Fodor
The focus of the present research is to analyse the factors that determine the purchase of Hungarian food. In our view, the preference for Hungarian food products can have economic, social and environmental benefits, which justify the investigation of how to rationalise these products. We believe that, in addition to product labelling and some community marketing activities, there is a need to focus on targeted marketing communication. The results of our quantitative primary research provide a starting point for this communication start-up by giving specific indications and suggestions on the content of the message, the communication channel and possible non-traditional (BTL) means. We see the practical utility of the results in defining the pillars of campaigns that can be implemented among potential target groups to reinforce consumer ethnocentrism.
{"title":"Hungarian food purchasing behaviour and promotion opportunities in the light of primary data","authors":"Anett Popovics, Mónika Garai-Fodor","doi":"10.1109/SACI58269.2023.10158568","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158568","url":null,"abstract":"The focus of the present research is to analyse the factors that determine the purchase of Hungarian food. In our view, the preference for Hungarian food products can have economic, social and environmental benefits, which justify the investigation of how to rationalise these products. We believe that, in addition to product labelling and some community marketing activities, there is a need to focus on targeted marketing communication. The results of our quantitative primary research provide a starting point for this communication start-up by giving specific indications and suggestions on the content of the message, the communication channel and possible non-traditional (BTL) means. We see the practical utility of the results in defining the pillars of campaigns that can be implemented among potential target groups to reinforce consumer ethnocentrism.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"506 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122818958","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158542
László Lindenmaier, Balázs Czibere, S. Aradi, Tamás Bécsi
There is an increasing demand for fully autonomous driving with the spread of advanced driver assistance systems. However, a higher level of automation requires an enhanced environment perception system. The automotive smart sensors detecting the surrounding objects are usually subject to various uncertainties. Objects are sometimes misdetected, false detections may also occur, and the sensor measurements are noisy. Multi-object tracking algorithms aim to compensate for these uncertainties, estimating precisely and continuously the state of surrounding objects. The real-time execution of these algorithms is crucial in automotive applications. This paper presents an improved runtime-efficient local nearest neighbor-based approach. The performance metrics of the proposed method get close to the state-of-the-art algorithms, besides having significantly lower computational complexity.
{"title":"A Runtime-Efficient Multi-Object Tracking Approach for Automotive Perception Systems","authors":"László Lindenmaier, Balázs Czibere, S. Aradi, Tamás Bécsi","doi":"10.1109/SACI58269.2023.10158542","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158542","url":null,"abstract":"There is an increasing demand for fully autonomous driving with the spread of advanced driver assistance systems. However, a higher level of automation requires an enhanced environment perception system. The automotive smart sensors detecting the surrounding objects are usually subject to various uncertainties. Objects are sometimes misdetected, false detections may also occur, and the sensor measurements are noisy. Multi-object tracking algorithms aim to compensate for these uncertainties, estimating precisely and continuously the state of surrounding objects. The real-time execution of these algorithms is crucial in automotive applications. This paper presents an improved runtime-efficient local nearest neighbor-based approach. The performance metrics of the proposed method get close to the state-of-the-art algorithms, besides having significantly lower computational complexity.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121452752","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158601
Márton Jagicza, Gábor László Tóth, Dávid Józsa, Letícia Pekk, Dénes Fodor
In terms of vehicle radars, the most important properties of targets are speed, distance, and radar cross section. Based on the Radar Cross Section (RCS), the type of the object can be identified with a good approximation: pedestrian, bicycle, car, truck even in extreme weather conditions. A radar cross section measures the reflectivity of an object and its numerical value is equal to the area of the cross section of a conducting sphere with the same reflectivity. Its value depends on the material and shape of the object, the angle of illumination, and the ratio between the wavelength and the size of the object. The article presents a measurement system for radar targets, the main component of which is an automotive radar. In addition, the evaluation software for the measurement system, which was created in the MATLAB / SIMULINK environment, will be presented. The measurement system was used to perform various measurements on the ZalaZONE Automotive Proving Ground (Zalaegerszeg, HUNGARY), the evaluation of which will be presented. The purpose of the measurements is to collect information about the radar cross-section values of pedestrians at different distances from the vehicle and dummies simulating them. A comparison of different pedestrians is presented. After that, we will show how even if a puppet is formally similar to a pedestrian, the RCS can show a different value.
{"title":"Measurement of Pedestrian Targets in Terms of Radar Cross Section","authors":"Márton Jagicza, Gábor László Tóth, Dávid Józsa, Letícia Pekk, Dénes Fodor","doi":"10.1109/SACI58269.2023.10158601","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158601","url":null,"abstract":"In terms of vehicle radars, the most important properties of targets are speed, distance, and radar cross section. Based on the Radar Cross Section (RCS), the type of the object can be identified with a good approximation: pedestrian, bicycle, car, truck even in extreme weather conditions. A radar cross section measures the reflectivity of an object and its numerical value is equal to the area of the cross section of a conducting sphere with the same reflectivity. Its value depends on the material and shape of the object, the angle of illumination, and the ratio between the wavelength and the size of the object. The article presents a measurement system for radar targets, the main component of which is an automotive radar. In addition, the evaluation software for the measurement system, which was created in the MATLAB / SIMULINK environment, will be presented. The measurement system was used to perform various measurements on the ZalaZONE Automotive Proving Ground (Zalaegerszeg, HUNGARY), the evaluation of which will be presented. The purpose of the measurements is to collect information about the radar cross-section values of pedestrians at different distances from the vehicle and dummies simulating them. A comparison of different pedestrians is presented. After that, we will show how even if a puppet is formally similar to a pedestrian, the RCS can show a different value.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129304356","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158616
M. Dmitriev, György Morva, P. Kádár
In recent years, the laying of 6-500 kV cable lines in polymer pipes has become widespread. This solution allows to minimize the amount of excavation, to cross various communications and barriers, to provide mechanical protection of cables. However, as experience has shown, polymer pipes have a significant drawback – they prevent to identify the presence of defects in the cable outer sheath and determine the exact location of these defects along the line route.
{"title":"Testing of 6-500 kV Cables in Polymer Pipes","authors":"M. Dmitriev, György Morva, P. Kádár","doi":"10.1109/SACI58269.2023.10158616","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158616","url":null,"abstract":"In recent years, the laying of 6-500 kV cable lines in polymer pipes has become widespread. This solution allows to minimize the amount of excavation, to cross various communications and barriers, to provide mechanical protection of cables. However, as experience has shown, polymer pipes have a significant drawback – they prevent to identify the presence of defects in the cable outer sheath and determine the exact location of these defects along the line route.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116052297","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158535
Péter Mogyorósi, S. Szénási
Nowadays, the approaches and methods of data storage have entirely changed from the traditional SQL-based theorem. The purpose of subsequent data processing has become one of the main aspects. NoSQL databases appeared, which enabled more abstract databases such as graph and time series databases. This paper aims to inspect the benefits of a database principle that works natively on the graphics card, which can be optimal for storing and querying spatial data. This survey introduces the HDF5 file format as a binary data store method, the postGIS system as one of the most widespread GIS data storage methods and the NVIDIA GPUDirect Storage (GDS), which is the high-level concept for enable DMA between the memory of the GPU and with the PCIe devices (e.g. NVME SSD) on Linux. Another objective of the paper is to present which features of these technologies can support the native GPU database concept [7], [8].
{"title":"GPU Database for Large Geospatial Datasets","authors":"Péter Mogyorósi, S. Szénási","doi":"10.1109/SACI58269.2023.10158535","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158535","url":null,"abstract":"Nowadays, the approaches and methods of data storage have entirely changed from the traditional SQL-based theorem. The purpose of subsequent data processing has become one of the main aspects. NoSQL databases appeared, which enabled more abstract databases such as graph and time series databases. This paper aims to inspect the benefits of a database principle that works natively on the graphics card, which can be optimal for storing and querying spatial data. This survey introduces the HDF5 file format as a binary data store method, the postGIS system as one of the most widespread GIS data storage methods and the NVIDIA GPUDirect Storage (GDS), which is the high-level concept for enable DMA between the memory of the GPU and with the PCIe devices (e.g. NVME SSD) on Linux. Another objective of the paper is to present which features of these technologies can support the native GPU database concept [7], [8].","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122024690","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158596
C. Braun, Aniketh Ramesh, S. Rothfuss, Manolis Chiou, Rustam Stolkin, S. Hohmann
Adjusting operator support in human-machine systems is a promising way of combining operator involvement with high overall system performance. Adaptive automation aims to achieve this goal without burdening the operator with the task of selecting and setting the desired amount of support. In this work, two novel adaptive automations are presented. We use the performance measure of “robot health” to formulate the optimal control problem of maximizing the robot health of a human-robot system through the adaption of operator support to develop two model predictive controllers. The first one considers discrete levels of operator support, or levels of automation, the second one uses the continuous conception of the degree of automation. We report on a proof-of-concept simulation study evaluating the proposed model predictive controllers in a collaborative teleoperation of a mobile robot; the results demonstrate the ability of both model predictive controllers to successfully arbitrate control between the operator and the robot’s controller to maximize robot health.
{"title":"Model Predictive Control of the Degree of Automation Optimizing Robot Health","authors":"C. Braun, Aniketh Ramesh, S. Rothfuss, Manolis Chiou, Rustam Stolkin, S. Hohmann","doi":"10.1109/SACI58269.2023.10158596","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158596","url":null,"abstract":"Adjusting operator support in human-machine systems is a promising way of combining operator involvement with high overall system performance. Adaptive automation aims to achieve this goal without burdening the operator with the task of selecting and setting the desired amount of support. In this work, two novel adaptive automations are presented. We use the performance measure of “robot health” to formulate the optimal control problem of maximizing the robot health of a human-robot system through the adaption of operator support to develop two model predictive controllers. The first one considers discrete levels of operator support, or levels of automation, the second one uses the continuous conception of the degree of automation. We report on a proof-of-concept simulation study evaluating the proposed model predictive controllers in a collaborative teleoperation of a mobile robot; the results demonstrate the ability of both model predictive controllers to successfully arbitrate control between the operator and the robot’s controller to maximize robot health.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127793786","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158670
Zsolt Krutilla, Attila Kovari
Natural Language Processing nowadays provides scientists with many research areas and opportunities, but as with most applied sciences, our goal in Natural Language Processing is to refine the underlying science and technology until it can be used reliably for business purposes. Transformer models, such as GPT or BERT, are currently showing outstanding results in the field of natural-language processing, but they require huge computational power and data to teach, but these conditions can only be met by larger research centers and large companies, and their inaccuracy makes them unsuitable for use as a ‘business as usual’ (BAU) solution. In this paper, we present a solution that is able to overcome these problems by focusing on accuracy and usability, and that can also bring a new perspective to the process of teaching deep learning models.
{"title":"How we can use text classification in the Back-Office environment of a bank as ‘business as usual’ solution","authors":"Zsolt Krutilla, Attila Kovari","doi":"10.1109/SACI58269.2023.10158670","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158670","url":null,"abstract":"Natural Language Processing nowadays provides scientists with many research areas and opportunities, but as with most applied sciences, our goal in Natural Language Processing is to refine the underlying science and technology until it can be used reliably for business purposes. Transformer models, such as GPT or BERT, are currently showing outstanding results in the field of natural-language processing, but they require huge computational power and data to teach, but these conditions can only be met by larger research centers and large companies, and their inaccuracy makes them unsuitable for use as a ‘business as usual’ (BAU) solution. In this paper, we present a solution that is able to overcome these problems by focusing on accuracy and usability, and that can also bring a new perspective to the process of teaching deep learning models.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124915974","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158661
Mahsa Dehghan Manshadi, Milad Mousavi, Arian Golzarian, M. Soltani, Amir H. Mosavi
Increasing demands for artificial intelligence tools in the medical sector show the huge interest of physicians. In recent years, one of the most effective assistant systems in this field is the real-time detection of early-stage colorectal polyps during colonoscopy. Since even experienced physicians may miss polyps during colonoscopy, the real-time assistance system is designed to prevent this and hence contributes to diminish the number of missed critical cases. One challenge in this field is the detection of false positives. These systems are prone to mistake artifacts for colorectal polyps. This review provides an overview over current quality assessment and restoration techniques to make a high-quality training dataset for training deep neural network algorithms. Furthermore, four of the latest, fastest, and most accurate methods are introduced and analyzed in the rest of the review. Our main contribution is to provide an analysis of current methods used to detect colorectal polyps. We present a list of available datasets and present a range of challenges colorectal cancer detection systems face.
{"title":"Colorectal Polyp Localization: From Image Restoration to Real-time Detection with Deep Learning","authors":"Mahsa Dehghan Manshadi, Milad Mousavi, Arian Golzarian, M. Soltani, Amir H. Mosavi","doi":"10.1109/SACI58269.2023.10158661","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158661","url":null,"abstract":"Increasing demands for artificial intelligence tools in the medical sector show the huge interest of physicians. In recent years, one of the most effective assistant systems in this field is the real-time detection of early-stage colorectal polyps during colonoscopy. Since even experienced physicians may miss polyps during colonoscopy, the real-time assistance system is designed to prevent this and hence contributes to diminish the number of missed critical cases. One challenge in this field is the detection of false positives. These systems are prone to mistake artifacts for colorectal polyps. This review provides an overview over current quality assessment and restoration techniques to make a high-quality training dataset for training deep neural network algorithms. Furthermore, four of the latest, fastest, and most accurate methods are introduced and analyzed in the rest of the review. Our main contribution is to provide an analysis of current methods used to detect colorectal polyps. We present a list of available datasets and present a range of challenges colorectal cancer detection systems face.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121896801","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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