Pub Date : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230988
M. Kamruzzaman, M. Arifuzzaman, Md. Saiful Islam
In this research we propose a moderate caching policy, in which the most popular or requested data will be stored in lower level access point routers of network. Data will be sorted as name-wise that reduces the searching time. Due to reduction of searching time, the power consumption is substantially reduces and the user will get fast response. Moreover, our new architectural design will improve the mobility to user. If users change the position after requesting data, the users may loss the lower level access point routers connectivity. But In new star network topology the user can get the data from other side's lower level access point routers. That increases the possibility of get popular data in the other lower level access point routers in the same network. This may help users to get desired data in shorter time. There for the mobility will be increased. We also design the network for YouTube. Most naturally, when client requests for data, then it comes from the server. But we assume that if user can get the data from intermediate node then link utilization will be reduced and power will be saved, response time will be shorter and node data will be performed as backup.
{"title":"Fast Response and Energy Efficient Caching Policy for Information Centric Networking with Flexible User Mobility","authors":"M. Kamruzzaman, M. Arifuzzaman, Md. Saiful Islam","doi":"10.1109/TENSYMP50017.2020.9230988","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230988","url":null,"abstract":"In this research we propose a moderate caching policy, in which the most popular or requested data will be stored in lower level access point routers of network. Data will be sorted as name-wise that reduces the searching time. Due to reduction of searching time, the power consumption is substantially reduces and the user will get fast response. Moreover, our new architectural design will improve the mobility to user. If users change the position after requesting data, the users may loss the lower level access point routers connectivity. But In new star network topology the user can get the data from other side's lower level access point routers. That increases the possibility of get popular data in the other lower level access point routers in the same network. This may help users to get desired data in shorter time. There for the mobility will be increased. We also design the network for YouTube. Most naturally, when client requests for data, then it comes from the server. But we assume that if user can get the data from intermediate node then link utilization will be reduced and power will be saved, response time will be shorter and node data will be performed as backup.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"35 1","pages":"1482-1485"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73548013","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230762
Shounak Kundu, M. Desarkar, P. K. Srijith
Timely forecast of traffic is very much needed for smart cities, which allows travelers and government agencies to make various decisions based on traffic flow. This will result in reduced traffic congestion and carbon dioxide emission. However, traffic forecasting is a challenging task due to the highly complex traffic pattern. Standard time series techniques may not be able to capture the nonlinear and noisy nature of the traffic flow. In this paper, we investigate how the deep learning models capture these characteristics and provide better predictive performance over standard time series and regression models. We compare the performances of state-of-the-art deep learning models on two traffic flow data sets and show their effectiveness in traffic flow prediction over traditional models.
{"title":"Traffic Forecasting with Deep Learning","authors":"Shounak Kundu, M. Desarkar, P. K. Srijith","doi":"10.1109/TENSYMP50017.2020.9230762","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230762","url":null,"abstract":"Timely forecast of traffic is very much needed for smart cities, which allows travelers and government agencies to make various decisions based on traffic flow. This will result in reduced traffic congestion and carbon dioxide emission. However, traffic forecasting is a challenging task due to the highly complex traffic pattern. Standard time series techniques may not be able to capture the nonlinear and noisy nature of the traffic flow. In this paper, we investigate how the deep learning models capture these characteristics and provide better predictive performance over standard time series and regression models. We compare the performances of state-of-the-art deep learning models on two traffic flow data sets and show their effectiveness in traffic flow prediction over traditional models.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"37 2 1","pages":"1074-1077"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78058105","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230864
Dipanjan Sen, Bijoy Goswami, Anup Dey, Priyanka Saha, S. Sarkar
This article demonstrates a simulation based analysis of sensitivity parameter of AlxGa1-xAs/GaAs Junction-less Double Gate MOSFET (DG-MOSFET) in the form of a biosensor by considering the Nano-Gap Filling and Self-Heating issue. In this work, a Nano-Gap has been introduced in the gate oxide region which acts as a cavity for trapping the bio-particles or biomolecules. Also, the sensitivity of the biosensor has been taken under consideration by incorporating the dielectric modulation method. Hence, the complete performance of the device has been evaluated by introducing the Nano-Gap Filling factor and Temperature Variation. Simulations have been performed extensively by using SILVACO ATLAS TCAD tool. Threshold Voltage change or AVTH is used as the sensitivity parameter, which shows highest sensitivity in case of 100% (Fully Filled) filled Nano-Gap at a low voltage (VDs=0.2V). Thus, the addressed issues will help in the realization of biosensors for early detection of diseases.
{"title":"Impact of Self-Heating and Nano-Gap Filling Factor on AlGaAs/GaAs Junction-Less DG-MOSFET Based Biosensor for Early Stage Diagnostics","authors":"Dipanjan Sen, Bijoy Goswami, Anup Dey, Priyanka Saha, S. Sarkar","doi":"10.1109/TENSYMP50017.2020.9230864","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230864","url":null,"abstract":"This article demonstrates a simulation based analysis of sensitivity parameter of AlxGa1-xAs/GaAs Junction-less Double Gate MOSFET (DG-MOSFET) in the form of a biosensor by considering the Nano-Gap Filling and Self-Heating issue. In this work, a Nano-Gap has been introduced in the gate oxide region which acts as a cavity for trapping the bio-particles or biomolecules. Also, the sensitivity of the biosensor has been taken under consideration by incorporating the dielectric modulation method. Hence, the complete performance of the device has been evaluated by introducing the Nano-Gap Filling factor and Temperature Variation. Simulations have been performed extensively by using SILVACO ATLAS TCAD tool. Threshold Voltage change or AVTH is used as the sensitivity parameter, which shows highest sensitivity in case of 100% (Fully Filled) filled Nano-Gap at a low voltage (VDs=0.2V). Thus, the addressed issues will help in the realization of biosensors for early detection of diseases.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"19 1","pages":"662-665"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78237718","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230951
S. Islam, M. Nurullah, M. Samsuzzaman
The notion of maturity is very crucial to obtain a good storage period of septic fruits and vegetables. It is possible to profess the maturity of fruit by various characteristics where color of the skin is the most standard measure for judging maturity. Typically, human's perception can be wrong about the maturity while the perception being made by visualizing the skin color. This research aims to develop a technique to detect and specify the status of mango into different stages. The collected RGB images are converted to HSV color space at the very first phase of the conducted research. By considering the “S” channel, the obtained image is segmented where thresholding technique is used. From the segmented image fifteen vital features are extracted. Three as well as six stage maturity classifications are performed based on these features with 94 and 88 percent of accuracy accordingly. The accuracy of result indicates that the proposed technique can be a helping hand to promote our mango fruit industry as well as our economy.
{"title":"Mango Fruit's Maturity Status Specification Based on Machine Learning using Image Processing","authors":"S. Islam, M. Nurullah, M. Samsuzzaman","doi":"10.1109/TENSYMP50017.2020.9230951","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230951","url":null,"abstract":"The notion of maturity is very crucial to obtain a good storage period of septic fruits and vegetables. It is possible to profess the maturity of fruit by various characteristics where color of the skin is the most standard measure for judging maturity. Typically, human's perception can be wrong about the maturity while the perception being made by visualizing the skin color. This research aims to develop a technique to detect and specify the status of mango into different stages. The collected RGB images are converted to HSV color space at the very first phase of the conducted research. By considering the “S” channel, the obtained image is segmented where thresholding technique is used. From the segmented image fifteen vital features are extracted. Three as well as six stage maturity classifications are performed based on these features with 94 and 88 percent of accuracy accordingly. The accuracy of result indicates that the proposed technique can be a helping hand to promote our mango fruit industry as well as our economy.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"94 1","pages":"1355-1358"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74918078","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230841
Md. Ehtesham Adnan, Mir Md Nur E Alam, Jannatul Ferdousi Sirajum Monira, Mohammad Rezaul Islam
The process of learning is very strenuous for the people who are visually impaired or visually challenged. Voice Activated Braille is a portable device that will help visually impaired or visually challenged people to learn Braille language without the help of others. This is an Arduino controlled solenoid-based device that will be able to guide visually impaired people to learn and read braille alphabets and eventually educate themselves to become a part of the regular workforce. This project will enable the visually impaired people to get benefits from the innovative braille techniques and discuss some representative examples to illustrate how this device can be utilized to address the educational problem of visually impaired and visually challenged people. This device is cheap, portable and is easy to use; contributing greatly in reducing the educational obstructions of visually impaired people and give them a sort of freedom.
{"title":"A Cost-Effective Voice Controlled Electronic Braille for Independent Learning of Visually Impaired People","authors":"Md. Ehtesham Adnan, Mir Md Nur E Alam, Jannatul Ferdousi Sirajum Monira, Mohammad Rezaul Islam","doi":"10.1109/TENSYMP50017.2020.9230841","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230841","url":null,"abstract":"The process of learning is very strenuous for the people who are visually impaired or visually challenged. Voice Activated Braille is a portable device that will help visually impaired or visually challenged people to learn Braille language without the help of others. This is an Arduino controlled solenoid-based device that will be able to guide visually impaired people to learn and read braille alphabets and eventually educate themselves to become a part of the regular workforce. This project will enable the visually impaired people to get benefits from the innovative braille techniques and discuss some representative examples to illustrate how this device can be utilized to address the educational problem of visually impaired and visually challenged people. This device is cheap, portable and is easy to use; contributing greatly in reducing the educational obstructions of visually impaired people and give them a sort of freedom.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"14 1","pages":"1317-1320"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74722004","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230907
Asraf Hossain Patoary, Md. Jahid Bin Kibria, Abdul Kaium
Parts-of-Speech(POS) tagging is the technique to assign each word in a sentence as an individual part of speech. POS tagging is the first important step in Natural Language Processing applications (NLP). In some languages, POS tagging works well with higher accuracy, but in the Bengali language, it is still an unsolved problem. The Bengali language is much ambiguous and inflectional, where every word has many more variants based on their suffixes and prefixes. Although developing POS tagging is not new for the Bengali language, we aim to make a highly accurate model with a minimal dataset. Here we developed a deep learning model, and it is mainly based on suffixes, which are parts of Bengali grammar. Moreover, we did experiment with a Bengali corpus that contains 2927 words with their corresponding parts of speech tags. The accuracy of our proposed POS tagging deep learning model is 93.90%. We also included this model as a python package to our open-source Bengali Natural language processing toolkit (BNLTK), which is now live on pipy.org.
{"title":"Implementation of Automated Bengali Parts of Speech Tagger: An Approach Using Deep Learning Algorithm","authors":"Asraf Hossain Patoary, Md. Jahid Bin Kibria, Abdul Kaium","doi":"10.1109/TENSYMP50017.2020.9230907","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230907","url":null,"abstract":"Parts-of-Speech(POS) tagging is the technique to assign each word in a sentence as an individual part of speech. POS tagging is the first important step in Natural Language Processing applications (NLP). In some languages, POS tagging works well with higher accuracy, but in the Bengali language, it is still an unsolved problem. The Bengali language is much ambiguous and inflectional, where every word has many more variants based on their suffixes and prefixes. Although developing POS tagging is not new for the Bengali language, we aim to make a highly accurate model with a minimal dataset. Here we developed a deep learning model, and it is mainly based on suffixes, which are parts of Bengali grammar. Moreover, we did experiment with a Bengali corpus that contains 2927 words with their corresponding parts of speech tags. The accuracy of our proposed POS tagging deep learning model is 93.90%. We also included this model as a python package to our open-source Bengali Natural language processing toolkit (BNLTK), which is now live on pipy.org.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"39 1","pages":"308-311"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73396846","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230653
Sumaiya, Md. Armanuzzaman
The execution of (ERISE) framework depends on proficient feature extraction and exact recovery of comparative enhancement of resulting images. This paper represents a brief investigation of the main techniques utilized for every image recovery, whereas indicating the importance of this rising innovation. Due to the alarming growth of the Web and the brightly high volume of information, we extend the method of CBIR - Content-Based Image Retrieval system by adding an extra dimension of enhancement. The point of this paper is also to create a framework design to back querying for exceptionally huge image databases with user-specified distance measures that can be utilized for a wide assortment of datasets in the domain of image enhancement. A large number of image query results image retrieval by query image but image quality may affect sometimes. That's why it's much important to enhance the image quality for better usage of an image when needed. The methodology illustrates the authenticity of this current methodology's convenience by differentiating out its efficiency from current methodologies.
{"title":"Enhancement of Resulting Image Search Engine (ERISE) by Content-Based Image Retrieval System","authors":"Sumaiya, Md. Armanuzzaman","doi":"10.1109/TENSYMP50017.2020.9230653","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230653","url":null,"abstract":"The execution of (ERISE) framework depends on proficient feature extraction and exact recovery of comparative enhancement of resulting images. This paper represents a brief investigation of the main techniques utilized for every image recovery, whereas indicating the importance of this rising innovation. Due to the alarming growth of the Web and the brightly high volume of information, we extend the method of CBIR - Content-Based Image Retrieval system by adding an extra dimension of enhancement. The point of this paper is also to create a framework design to back querying for exceptionally huge image databases with user-specified distance measures that can be utilized for a wide assortment of datasets in the domain of image enhancement. A large number of image query results image retrieval by query image but image quality may affect sometimes. That's why it's much important to enhance the image quality for better usage of an image when needed. The methodology illustrates the authenticity of this current methodology's convenience by differentiating out its efficiency from current methodologies.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"70 4 1","pages":"1416-1419"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74026938","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230713
Palash Sarkar, Raja Rashidul Hasan, Sourav Sinha, M. Rahman, T. R. Niloy
In this paper, an on-body patch antenna is proposed, which is designed based on Snap-On button. The antenna will operate at ISM (2.4 GHz to 2.48 GHz) band with resonant frequency of 2.413 GHz. FR 408 is used as a substrate and pure copper as patch. The performance of antenna has been analyzed with two different textile materials of cotton and wool. A human phantom model is created with layer of skin, fat and muscle for tasting the antenna in Bio environment. S11 is found to be −15.18 dB and −15.17 dB for cotton and wool respectively on human phantom body. SAR is also observed for ensuring safety during on body applications and found 0.134W/kg and 0.136W/kg. All design and testing is simulated in CST STUDIO SUITE.
{"title":"A Wearable Snap-on Button Antenna for on Body Application","authors":"Palash Sarkar, Raja Rashidul Hasan, Sourav Sinha, M. Rahman, T. R. Niloy","doi":"10.1109/TENSYMP50017.2020.9230713","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230713","url":null,"abstract":"In this paper, an on-body patch antenna is proposed, which is designed based on Snap-On button. The antenna will operate at ISM (2.4 GHz to 2.48 GHz) band with resonant frequency of 2.413 GHz. FR 408 is used as a substrate and pure copper as patch. The performance of antenna has been analyzed with two different textile materials of cotton and wool. A human phantom model is created with layer of skin, fat and muscle for tasting the antenna in Bio environment. S11 is found to be −15.18 dB and −15.17 dB for cotton and wool respectively on human phantom body. SAR is also observed for ensuring safety during on body applications and found 0.134W/kg and 0.136W/kg. All design and testing is simulated in CST STUDIO SUITE.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"39 1","pages":"1498-1501"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79261927","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230721
Md Sakibul Islam, Fahmid Shahriar Iqbal, Muhaimenul Islam
Registration process regarding ownership, possession or other rights for properties like land is a tedious method in progressing countries like Bangladesh. This paper highlights issues related to manual land registrations processes such as transparency, centralization, authenticity, reliability, etc and proposes a better method to overcome these problems using Blockchain Technology. The comparison between Blockchain-based digital land record systems in different countries is also explored in this paper. Finally, we have developed a novel framework that uses Blockchain method for executing the process of Land Registration and providing authentic and indisputable rights on ownership for the people in Bangladesh.
{"title":"A Novel Framework for Implementation of Land Registration and Ownership Management via Blockchain in Bangladesh","authors":"Md Sakibul Islam, Fahmid Shahriar Iqbal, Muhaimenul Islam","doi":"10.1109/TENSYMP50017.2020.9230721","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230721","url":null,"abstract":"Registration process regarding ownership, possession or other rights for properties like land is a tedious method in progressing countries like Bangladesh. This paper highlights issues related to manual land registrations processes such as transparency, centralization, authenticity, reliability, etc and proposes a better method to overcome these problems using Blockchain Technology. The comparison between Blockchain-based digital land record systems in different countries is also explored in this paper. Finally, we have developed a novel framework that uses Blockchain method for executing the process of Land Registration and providing authentic and indisputable rights on ownership for the people in Bangladesh.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"51 1","pages":"859-862"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84350531","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 : 2020-06-05DOI: 10.1109/TENSYMP50017.2020.9230861
A. Hoque, A. Farabi, Fahad Ahmed, M. Islam
Lung cancer is one of the most threatening diseases among all other lung disorders which is caused for uncontrolled cell growth. The detection of lung cancer in early stages is the main comprehensible approach to enhance patient's survival rate. Image Processing together with machine learning process and other technologies are used to study medical images for earlier detection and treatment of present clinical world. This research study proposed an automated approach where Computed Tomography (CT) images are used to identify lung cancer at its early stage. The main objective of this research study is to achieve standard performance accuracy. We have proposed a new framework for lung cancer diagnosis using various features extracted from computed tomography images where different steps are used like enhancement, median, filter, segmentation, feature extraction and support vector machine. Finally, the experiment result shows the accuracy performance of our proposed method.
{"title":"Automated Detection of Lung Cancer Using CT Scan Images","authors":"A. Hoque, A. Farabi, Fahad Ahmed, M. Islam","doi":"10.1109/TENSYMP50017.2020.9230861","DOIUrl":"https://doi.org/10.1109/TENSYMP50017.2020.9230861","url":null,"abstract":"Lung cancer is one of the most threatening diseases among all other lung disorders which is caused for uncontrolled cell growth. The detection of lung cancer in early stages is the main comprehensible approach to enhance patient's survival rate. Image Processing together with machine learning process and other technologies are used to study medical images for earlier detection and treatment of present clinical world. This research study proposed an automated approach where Computed Tomography (CT) images are used to identify lung cancer at its early stage. The main objective of this research study is to achieve standard performance accuracy. We have proposed a new framework for lung cancer diagnosis using various features extracted from computed tomography images where different steps are used like enhancement, median, filter, segmentation, feature extraction and support vector machine. Finally, the experiment result shows the accuracy performance of our proposed method.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"13 1","pages":"1030-1033"},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84617707","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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