%0 Journal Article %1 noauthororeditor %A Hossen, Md. Abdul Matin | Abdur Rahman | S M Abdullah Al Shuaeb | Anwar %D 2021 %J International Journal of Trend in Scientific Research and Development %K (CM) (IP) (ML) (SVM) Chest Confusion Covid-19 Image Learning Machine Matrix Processing Support Vector X-Ray %N 4 %P 626-632 %T Automatic Covid 19 Infected Chest X Ray Image Classification using Support Vector Machine %U https://www.ijtsrd.comcomputer-science/artificial-intelligence/41283/automatic-covid19-infected-chest-xray-image-classification-using-support-vector-machine/md-abdul-matin %V 5 %X The recent coronavirus disease COVID 19 is extending very speedily over the world for the sake of its very infectious nature and is announced nationwide by the world health organization WHO . The COVID 19 is a group of coronavirus that has caused panic all over the world. It enters people through the sneezing and coughing of the infected person and weakens the person and it then slowly infects the affected person’s lungs. In this study, we have classified the chest X Ray images like Covid 19 infected chest images or normal chest images. Classifying the chest X Ray images is hard and time consuming work for human beings. Hence, an automatic Covid 19 infected chest X Ray image or normal chest classification tool is very useful even for experience humans to classify a lot of chest X Ray images. For that, we have proposed a new machine learning technique to automatically classify the chest Covid 19 infected X Ray images or normal chest images. Hence, we have used a Machine learning ML model like Support Vector Machine SVM to classify Covid 19 infected chest images and normal chest images. For this work, at first, we have preprocessed the chest X Ray image. Then we have extracted the distinct features from the chest X Ray images. After that, these features have trained into Machine Learning ML algorithm and finally classify these images into the category. From the experiment, The Support Vector Machine SVM models achieving an accuracy of up to 93.1 . Md. Abdul Matin | Abdur Rahman | S M Abdullah Al Shuaeb | Anwar Hossen Äutomatic Covid-19 Infected Chest X-Ray Image Classification using Support Vector Machine" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41283.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41283/automatic-covid19-infected-chest-xray-image-classification-using-support-vector-machine/md-abdul-matin

@article{noauthororeditor, abstract = {The recent coronavirus disease COVID 19 is extending very speedily over the world for the sake of its very infectious nature and is announced nationwide by the world health organization WHO . The COVID 19 is a group of coronavirus that has caused panic all over the world. It enters people through the sneezing and coughing of the infected person and weakens the person and it then slowly infects the affected person’s lungs. In this study, we have classified the chest X Ray images like Covid 19 infected chest images or normal chest images. Classifying the chest X Ray images is hard and time consuming work for human beings. Hence, an automatic Covid 19 infected chest X Ray image or normal chest classification tool is very useful even for experience humans to classify a lot of chest X Ray images. For that, we have proposed a new machine learning technique to automatically classify the chest Covid 19 infected X Ray images or normal chest images. Hence, we have used a Machine learning ML model like Support Vector Machine SVM to classify Covid 19 infected chest images and normal chest images. For this work, at first, we have preprocessed the chest X Ray image. Then we have extracted the distinct features from the chest X Ray images. After that, these features have trained into Machine Learning ML algorithm and finally classify these images into the category. From the experiment, The Support Vector Machine SVM models achieving an accuracy of up to 93.1 . Md. Abdul Matin | Abdur Rahman | S M Abdullah Al Shuaeb | Anwar Hossen "Automatic Covid-19 Infected Chest X-Ray Image Classification using Support Vector Machine" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41283.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41283/automatic-covid19-infected-chest-xray-image-classification-using-support-vector-machine/md-abdul-matin }, added-at = {2021-07-15T09:51:31.000+0200}, author = {Hossen, Md. Abdul Matin | Abdur Rahman | S M Abdullah Al Shuaeb | Anwar}, biburl = {https://www.bibsonomy.org/bibtex/2f28e9494810b087be1db380ed879dc92/ijtsrd}, interhash = {1b5b686c997cafa443563ee04ef6b939}, intrahash = {f28e9494810b087be1db380ed879dc92}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {(CM) (IP) (ML) (SVM) Chest Confusion Covid-19 Image Learning Machine Matrix Processing Support Vector X-Ray}, language = {english}, month = jun, number = 4, pages = {626-632}, timestamp = {2021-07-15T09:51:31.000+0200}, title = {Automatic Covid 19 Infected Chest X Ray Image Classification using Support Vector Machine }, url = {https://www.ijtsrd.comcomputer-science/artificial-intelligence/41283/automatic-covid19-infected-chest-xray-image-classification-using-support-vector-machine/md-abdul-matin}, volume = 5, year = 2021 }