Pub Date : 2021-11-24DOI: 10.1109/CITISIA53721.2021.9719922
Aman Arora, S. Panda, J. Raheja, Dimple Nagpal
Unprecedented level of autonomy and highly efficient interpersonal communications amongst crewmembers are compulsorily norms for astronauts in all LDSE missions, again testing the psycho-emotional limits for the astronauts. The present communication reviews & outlines the role of social robots and HRI, and the recent advances in haptics and gesture-controlled systems, as well as their unique effectiveness and interventions in increasing the effectiveness of future LDSE missions. Multimodal Media Systems are used for Human Robot Interactions (HRI), including, facial & hand movements, speech, sounds, AV clips, physical touch and haptics. Various systems have been explored and evaluated, including ESAS, AAR, CIMON, PSA, Haptics and joystick modules and others. An HRI system needs to be developed ensuring all prerequisites of standardizes interactions including multi-spacial ranges, interaction architecture (task manager, interaction manager, resource manager, dialogue agent and robot agents), and constrained interfaces. Social HRI (sHRI) offers a fast evolving field and extensive work is being done on SSD, DSSD, multimodal systems, novel gesture control systems, humanoids and other options. The fast integration of sHRI with LDSE will definitely aid in advancing the efficacy of such missions.
{"title":"Development Approaches To Intuitive, SSD & Haptics Integrated HRI & Social HRI systems for Assisting Space Exploration","authors":"Aman Arora, S. Panda, J. Raheja, Dimple Nagpal","doi":"10.1109/CITISIA53721.2021.9719922","DOIUrl":"https://doi.org/10.1109/CITISIA53721.2021.9719922","url":null,"abstract":"Unprecedented level of autonomy and highly efficient interpersonal communications amongst crewmembers are compulsorily norms for astronauts in all LDSE missions, again testing the psycho-emotional limits for the astronauts. The present communication reviews & outlines the role of social robots and HRI, and the recent advances in haptics and gesture-controlled systems, as well as their unique effectiveness and interventions in increasing the effectiveness of future LDSE missions. Multimodal Media Systems are used for Human Robot Interactions (HRI), including, facial & hand movements, speech, sounds, AV clips, physical touch and haptics. Various systems have been explored and evaluated, including ESAS, AAR, CIMON, PSA, Haptics and joystick modules and others. An HRI system needs to be developed ensuring all prerequisites of standardizes interactions including multi-spacial ranges, interaction architecture (task manager, interaction manager, resource manager, dialogue agent and robot agents), and constrained interfaces. Social HRI (sHRI) offers a fast evolving field and extensive work is being done on SSD, DSSD, multimodal systems, novel gesture control systems, humanoids and other options. The fast integration of sHRI with LDSE will definitely aid in advancing the efficacy of such missions.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130255963","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719982
Samriddha Adikari, Jinfeng Su, Kamini (Simi) Bajaj,
The growth in the number of systems based on Internet of Things (IoT), real-time service and automation that can be provided to users is enormous in the last decade. One of the major obstacles in securing IoT based network is tracking and tracing cyber-attack events and their sources. The aim of this study is to analyze current research on deep learning-based network forensic optimization techniques using secondary research. Major findings are that deep learning technology can effectively identify attacks during data communication in IoT systems than the state-of-the-art methods. In this study, major components of the systems proposed by researchers were identified, presented in a table format and classified based on methodology which revealed that deep learning technology can identify attacks in IoT devices.
{"title":"Review of network-forensic analysis optimization using deep learning against attacks on IoT devices","authors":"Samriddha Adikari, Jinfeng Su, Kamini (Simi) Bajaj,","doi":"10.1109/citisia53721.2021.9719982","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719982","url":null,"abstract":"The growth in the number of systems based on Internet of Things (IoT), real-time service and automation that can be provided to users is enormous in the last decade. One of the major obstacles in securing IoT based network is tracking and tracing cyber-attack events and their sources. The aim of this study is to analyze current research on deep learning-based network forensic optimization techniques using secondary research. Major findings are that deep learning technology can effectively identify attacks during data communication in IoT systems than the state-of-the-art methods. In this study, major components of the systems proposed by researchers were identified, presented in a table format and classified based on methodology which revealed that deep learning technology can identify attacks in IoT devices.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121090295","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 : 2021-11-24DOI: 10.1109/CITISIA53721.2021.9719928
Gowind Misra, Kamini Bajaj
Supply chain management is the approach applied to track products, including the transformation process. Real-time tracing techniques are considered to enhance the accuracy and performance rate of the tracing process.The main contribution of this work consists of a review of real-time tracing techniques in supply management with focus on cloud computing, Information extracted supports the development of a taxonomy of evaluation and classification processes , process stages and the role blockchain technology plays in improving tracing and data handling. This work is based on secondary research into articles related to real-time tracing techniques and supply chain management.We contribute to the body of knowledge for tracing in supply chain management through an up-to-date snapshot of the extent and breadth of research in the field and through clear identification of remaining challenges to guide future research.
{"title":"Real-time supply chain tracing using blockchain from cloud-based computing portal","authors":"Gowind Misra, Kamini Bajaj","doi":"10.1109/CITISIA53721.2021.9719928","DOIUrl":"https://doi.org/10.1109/CITISIA53721.2021.9719928","url":null,"abstract":"Supply chain management is the approach applied to track products, including the transformation process. Real-time tracing techniques are considered to enhance the accuracy and performance rate of the tracing process.The main contribution of this work consists of a review of real-time tracing techniques in supply management with focus on cloud computing, Information extracted supports the development of a taxonomy of evaluation and classification processes , process stages and the role blockchain technology plays in improving tracing and data handling. This work is based on secondary research into articles related to real-time tracing techniques and supply chain management.We contribute to the body of knowledge for tracing in supply chain management through an up-to-date snapshot of the extent and breadth of research in the field and through clear identification of remaining challenges to guide future research.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127116784","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719936
Rekha Sharma, A. B. M. Mehedi Hasan, Jinfeng Su, Moshiur Bhuiyan
This This paper aims to increase the farmers’ income and enhance the productivity of farming day-by-day so that the agriculture industry can develop at a large scale. The objective of this research is to increase the farming and seed production for the farmers in agriculture by monitoring and computer network system with reliable servers. It is crucial to solve or minimize or avoid this problem to ensure the best farming and animal husbandry across the agriculture sector to maintain seed growth for the farmers and customers without any error and monitoring. The background for this study is to provide the best services of monitoring and computer networks globally for the production and growing sectors to be involved in emerging activities to reduce the errors using computer network monitoring. Even after dealing with these difficulties, ranchers need sizeable, stable business sectors for their harvests. Appropriately, in the last and present century, people groups have begun investigating the conceivable outcomes by embracing distinctive current procedures in agribusiness. The proposed solution will address the current challenges of computer network monitoring data across the agriculture sector to understand the actual outcomes.
{"title":"Improving Weeds Identification with a Repository of Agricultural Pre-trained Deep Neural Networks","authors":"Rekha Sharma, A. B. M. Mehedi Hasan, Jinfeng Su, Moshiur Bhuiyan","doi":"10.1109/citisia53721.2021.9719936","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719936","url":null,"abstract":"This This paper aims to increase the farmers’ income and enhance the productivity of farming day-by-day so that the agriculture industry can develop at a large scale. The objective of this research is to increase the farming and seed production for the farmers in agriculture by monitoring and computer network system with reliable servers. It is crucial to solve or minimize or avoid this problem to ensure the best farming and animal husbandry across the agriculture sector to maintain seed growth for the farmers and customers without any error and monitoring. The background for this study is to provide the best services of monitoring and computer networks globally for the production and growing sectors to be involved in emerging activities to reduce the errors using computer network monitoring. Even after dealing with these difficulties, ranchers need sizeable, stable business sectors for their harvests. Appropriately, in the last and present century, people groups have begun investigating the conceivable outcomes by embracing distinctive current procedures in agribusiness. The proposed solution will address the current challenges of computer network monitoring data across the agriculture sector to understand the actual outcomes.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132917517","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719940
Minh Nguyen, Phuong-Thai Nguyen, V. Nguyen, Quang-Minh Nguyen
Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the quality of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.
{"title":"Generating Product Description with Generative Pre-trained Transformer 2","authors":"Minh Nguyen, Phuong-Thai Nguyen, V. Nguyen, Quang-Minh Nguyen","doi":"10.1109/citisia53721.2021.9719940","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719940","url":null,"abstract":"Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the quality of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129371327","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719900
{"title":"IEEE CSU Student Branch Committee (2021)","authors":"","doi":"10.1109/citisia53721.2021.9719900","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719900","url":null,"abstract":"","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134033367","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719974
M. Thi, Le Hoang Son, Nguyen Tran Quoc Vinh, Nguyen Thi Huong Quynh
The study reviews current computing infrastructure of Internet-of-Things based applications in smart agriculture. The purpose is to identify key areas of state-of-arts computing technologies, data architecture, network technologies, and artificial intelligence, as well as ongoing challenges in these fields. To deliver the best of our knowledge, we review the latest research published in peer-reviewed journals and conferences from 2019 to 2021 depending on a four-step selection process of identification, screening, eligibility, and inclusion exclusion criteria. To examine these documents, a systematic review is conducted, and two main questions are answered. The output indicates that the improvements of computing infrastructure of IoT create exciting opportunities for real-world smart agriculture applications for evaluating, monitoring, enhancing the resource quality of nature such as soil, water, crop, etc. We conclude by summarizing that they are most commonly used in terms of network technologies, computing technologies, and data storage technologies of IoT. It could be considered like the kickoff point for the other forthcoming multi-disciplinary examination in smart applications and especially smart agriculture.
{"title":"Computing Infrastructure Of IoT Applications In Smart Agriculture: A Systematical Review","authors":"M. Thi, Le Hoang Son, Nguyen Tran Quoc Vinh, Nguyen Thi Huong Quynh","doi":"10.1109/citisia53721.2021.9719974","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719974","url":null,"abstract":"The study reviews current computing infrastructure of Internet-of-Things based applications in smart agriculture. The purpose is to identify key areas of state-of-arts computing technologies, data architecture, network technologies, and artificial intelligence, as well as ongoing challenges in these fields. To deliver the best of our knowledge, we review the latest research published in peer-reviewed journals and conferences from 2019 to 2021 depending on a four-step selection process of identification, screening, eligibility, and inclusion exclusion criteria. To examine these documents, a systematic review is conducted, and two main questions are answered. The output indicates that the improvements of computing infrastructure of IoT create exciting opportunities for real-world smart agriculture applications for evaluating, monitoring, enhancing the resource quality of nature such as soil, water, crop, etc. We conclude by summarizing that they are most commonly used in terms of network technologies, computing technologies, and data storage technologies of IoT. It could be considered like the kickoff point for the other forthcoming multi-disciplinary examination in smart applications and especially smart agriculture.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130481761","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719899
Muhammad Akmal, Binod Syangtan, Amr Alchouemi
The main aim of this report is to find how data security can be improved in a cloud environment using the remote data auditing technique. The research analysis of the existing journal articles that are peer-reviewed Q1 level of articles is selected to perform the analysis.The main taxonomy that is proposed in this project is being data, auditing, monitoring, and output i.e., DAMO taxonomy that is used and includes these components. The data component would include the type of data; the auditing would ensure the algorithm that would be used at the backend and the storage would include the type of database as single or the distributed server in which the data would be stored.As a result of this research, it would help understand how the data can be ensured to have the required level of privacy and security when the third-party database vendors would be used by the organizations to maintain their data. Since most of the organizations are looking to reduce their burden of the local level of data storage and to reduce the maintenance by the outsourcing of the cloud there are still many issues that occur when there comes the time to check if the data is accurate or not and to see if the data is stored with resilience. In such a case, there is a need to use the Remote Data Auditing techniques that are quite helpful to ensure that the data which is outsourced is reliable and maintained with integrity when the information is stored in the single or the distributed servers.
{"title":"Enhancing the security of data in cloud computing environments using Remote Data Auditing","authors":"Muhammad Akmal, Binod Syangtan, Amr Alchouemi","doi":"10.1109/citisia53721.2021.9719899","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719899","url":null,"abstract":"The main aim of this report is to find how data security can be improved in a cloud environment using the remote data auditing technique. The research analysis of the existing journal articles that are peer-reviewed Q1 level of articles is selected to perform the analysis.The main taxonomy that is proposed in this project is being data, auditing, monitoring, and output i.e., DAMO taxonomy that is used and includes these components. The data component would include the type of data; the auditing would ensure the algorithm that would be used at the backend and the storage would include the type of database as single or the distributed server in which the data would be stored.As a result of this research, it would help understand how the data can be ensured to have the required level of privacy and security when the third-party database vendors would be used by the organizations to maintain their data. Since most of the organizations are looking to reduce their burden of the local level of data storage and to reduce the maintenance by the outsourcing of the cloud there are still many issues that occur when there comes the time to check if the data is accurate or not and to see if the data is stored with resilience. In such a case, there is a need to use the Remote Data Auditing techniques that are quite helpful to ensure that the data which is outsourced is reliable and maintained with integrity when the information is stored in the single or the distributed servers.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122451319","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719897
Ira Nath, P. Biswas, Kankana Ganguly, Dharmpal Singh, S. M. Islam, Ton Quang Cuong, Souvik Pal
India is a highly densely populated country. India is facing a very serious challenge due to the novel COVID-I9 outbreak. In this situation, the economic state of the people is very unstable. Blockchain technology proves helpful to subdue the situation. A voting system with ballot papers is quite tuff now. It is very costly for the government. The pandemic may also spread very quickly. The system of developing ledger serves the idea of developments of a new e-voting system that is economical, easy to use, and highly secure. This paper proposes ways and solutions to design an e-voting system using blockchain technology. The paper's primary goal is to develop a highly secure e-voting technique using which people can cast their valuable votes from their home, working place - anywhere from the world. This e-voting technique is least costly, highly secure, and able to prevent further spreading of any infectious disease in the near future. In this paper, an e-voting system using blockchain has been designed to overcome all these difficulties mentioned above during traditional voting using ballot. The significance of the proposed work is to design of a highly safe and least costly e- voting system using blockchain. Using this system the people can cast their vote easily, securely and without wasting any time. Casting vote will be now just from few clicks away and from any place with a stable internet connection.
{"title":"A Heuristic Approach using Block Chain to Fight Novel COVID-19 During an Election","authors":"Ira Nath, P. Biswas, Kankana Ganguly, Dharmpal Singh, S. M. Islam, Ton Quang Cuong, Souvik Pal","doi":"10.1109/citisia53721.2021.9719897","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719897","url":null,"abstract":"India is a highly densely populated country. India is facing a very serious challenge due to the novel COVID-I9 outbreak. In this situation, the economic state of the people is very unstable. Blockchain technology proves helpful to subdue the situation. A voting system with ballot papers is quite tuff now. It is very costly for the government. The pandemic may also spread very quickly. The system of developing ledger serves the idea of developments of a new e-voting system that is economical, easy to use, and highly secure. This paper proposes ways and solutions to design an e-voting system using blockchain technology. The paper's primary goal is to develop a highly secure e-voting technique using which people can cast their valuable votes from their home, working place - anywhere from the world. This e-voting technique is least costly, highly secure, and able to prevent further spreading of any infectious disease in the near future. In this paper, an e-voting system using blockchain has been designed to overcome all these difficulties mentioned above during traditional voting using ballot. The significance of the proposed work is to design of a highly safe and least costly e- voting system using blockchain. Using this system the people can cast their vote easily, securely and without wasting any time. Casting vote will be now just from few clicks away and from any place with a stable internet connection.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115358643","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 : 2021-11-24DOI: 10.1109/citisia53721.2021.9719963
S. Tiwari, S. Abdullah, Rashidul Mubasher, A. Alsadoon, P. Prasad
Deep learning based on lung cancer classification has been used increasingly for the early diagnosis for several reasons such as lack of robust deep learning-based system, complexity of nodule structure, lack of proper lung segmentation technique, high false positive result, lack of best feature extraction and less amount of medical imaging data for training deep learning model, it has been difficult to get high classification performance. The aim of this paper getting high lung cancer classification performance. We introduce the Data, Classification technique and View (DCV) as main components of the system that concern for the better lung cancer classification results, along with them different intermediate components such as Lung nodule segmentation, Feature extraction, Feature reduction are also defined. These components are key for providing better classification performance result which helps radiologist for early diagnosis of lung cancer. We have proposed uses image data having different dimensionality as input to the deep learning based classifier which provides lung cancer classification to be viewed by radiologists for the early diagnosis of lung cancer.We evaluated the proposed DCV system by classifying 30 state-of-art research papers in the field of deep learning based lung cancer classification system. Through this paper, readers will get the result of deep learning based lung cancer classification system. Also, readers will understand the classification groups, validation criteria, future gaps of the 30 literature.
基于深度学习的肺癌分类越来越多地用于早期诊断，但由于基于深度学习的系统缺乏鲁棒性、结节结构复杂、缺乏适当的肺分割技术、假阳性结果高、缺乏最佳特征提取以及用于训练深度学习模型的医学影像数据量少等原因，难以获得较高的分类性能。本文的目的是获得较高的肺癌分类性能。我们引入了数据、分类技术和视图(Data, Classification technology and View, DCV)作为系统的主要组成部分，关注更好的肺癌分类结果，并定义了肺结节分割、特征提取、特征约简等不同的中间组成部分。这些组成部分是提供更好的分类性能结果的关键，有助于放射科医生早期诊断肺癌。我们建议使用具有不同维度的图像数据作为基于深度学习的分类器的输入，该分类器提供肺癌分类，供放射科医生用于肺癌的早期诊断。我们通过对基于深度学习的肺癌分类系统领域的30篇最新研究论文进行分类来评估所提出的DCV系统。通过本文，读者将得到基于深度学习的肺癌分类系统的结果。同时，读者将了解30篇文献的分类分组、验证标准、未来差距。
{"title":"DCV: A Taxonomy on Deep Learning Based Lung Cancer Classification","authors":"S. Tiwari, S. Abdullah, Rashidul Mubasher, A. Alsadoon, P. Prasad","doi":"10.1109/citisia53721.2021.9719963","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719963","url":null,"abstract":"Deep learning based on lung cancer classification has been used increasingly for the early diagnosis for several reasons such as lack of robust deep learning-based system, complexity of nodule structure, lack of proper lung segmentation technique, high false positive result, lack of best feature extraction and less amount of medical imaging data for training deep learning model, it has been difficult to get high classification performance. The aim of this paper getting high lung cancer classification performance. We introduce the Data, Classification technique and View (DCV) as main components of the system that concern for the better lung cancer classification results, along with them different intermediate components such as Lung nodule segmentation, Feature extraction, Feature reduction are also defined. These components are key for providing better classification performance result which helps radiologist for early diagnosis of lung cancer. We have proposed uses image data having different dimensionality as input to the deep learning based classifier which provides lung cancer classification to be viewed by radiologists for the early diagnosis of lung cancer.We evaluated the proposed DCV system by classifying 30 state-of-art research papers in the field of deep learning based lung cancer classification system. Through this paper, readers will get the result of deep learning based lung cancer classification system. Also, readers will understand the classification groups, validation criteria, future gaps of the 30 literature.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116883595","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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