Pub Date : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640904
Sushant Singh, Ajay Kumar, S. Thenmalar
Managing one’s emotions in the workplace is more important nowadays than it ever has been. The current approach shows fluctuation in emotion prediction as there is a need for strong correlation between the input images and fused image, fluctuating illumination environments may impact the fitting process and lessen the recognition correctness, lack in training dataset. To address this problem, this paper explores different types of algorithms, neural networks and machine learning techniques which can be used as a base to increase the efficiency as well as the robustness of our model. The proposed model consists of modules, one will load the 48X48 pixel grayscale images of faces from FER2013 datasets, pre-process it and uses a CNN classifier to classify the acquired image into different emotion categories and the other module uses a Haar-Cascade feature to detect the face and predicts the corresponding emotions and displaying an audio or video recommendation in the output. This will help to analyse the sentimental state of an individual, providing robustness against low illumination, reducing fitting process.
{"title":"Facial Emotion Analysis and Recommendation Using CNN","authors":"Sushant Singh, Ajay Kumar, S. Thenmalar","doi":"10.1109/I-SMAC52330.2021.9640904","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640904","url":null,"abstract":"Managing one’s emotions in the workplace is more important nowadays than it ever has been. The current approach shows fluctuation in emotion prediction as there is a need for strong correlation between the input images and fused image, fluctuating illumination environments may impact the fitting process and lessen the recognition correctness, lack in training dataset. To address this problem, this paper explores different types of algorithms, neural networks and machine learning techniques which can be used as a base to increase the efficiency as well as the robustness of our model. The proposed model consists of modules, one will load the 48X48 pixel grayscale images of faces from FER2013 datasets, pre-process it and uses a CNN classifier to classify the acquired image into different emotion categories and the other module uses a Haar-Cascade feature to detect the face and predicts the corresponding emotions and displaying an audio or video recommendation in the output. This will help to analyse the sentimental state of an individual, providing robustness against low illumination, reducing fitting process.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133481712","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640915
Zhao Yuan
Logistics refers to the behavior of suppliers to meet customers' logistics needs by organizing and managing such basic functions as transportation, storage, loading and unloading, handling, packaging, circulation processing, and distribution. The concept of logistics was originally put forward by the United States. After nearly a century of theoretical and practical research, the United States has been at the forefront of the development of logistics in the world. In this paper, a variety of characteristics of quantum state in quantum theory are transplanted to algorithm theory, which greatly makes up for the lack of parallel computing ability of traditional algorithms, and provides an effective improvement method for traditional algorithms when they face increasingly complex engineering practical problems.
{"title":"Optimal Vehicle Scheduling of Logistics Distribution in Foreign Trade Enterprises based on Hybrid Quantum Genetic Algorithm","authors":"Zhao Yuan","doi":"10.1109/I-SMAC52330.2021.9640915","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640915","url":null,"abstract":"Logistics refers to the behavior of suppliers to meet customers' logistics needs by organizing and managing such basic functions as transportation, storage, loading and unloading, handling, packaging, circulation processing, and distribution. The concept of logistics was originally put forward by the United States. After nearly a century of theoretical and practical research, the United States has been at the forefront of the development of logistics in the world. In this paper, a variety of characteristics of quantum state in quantum theory are transplanted to algorithm theory, which greatly makes up for the lack of parallel computing ability of traditional algorithms, and provides an effective improvement method for traditional algorithms when they face increasingly complex engineering practical problems.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128836054","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640910
V. Nikam, S. Dhande
Nowadays security of information is highly important. Most of the IT industries have their focus on the security of data either stored on the server system or transmitted on wireless media. The objective of proposed work is to utilize the samples of carrier object so that data Hiding capacity a carrier should be maximized without changing samples the carrier. It also focuses on optimizing utilization of selected samples again and again for data hiding. The main idea of this paper is to concentrate on sample utilization and virtual Data Hiding & extraction. Obtained results from propose concept imply that, with virtual data replacement, there is no change in resultant stego object.
{"title":"Round Robin Scheduling for Virtual Data Hiding and Extraction","authors":"V. Nikam, S. Dhande","doi":"10.1109/I-SMAC52330.2021.9640910","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640910","url":null,"abstract":"Nowadays security of information is highly important. Most of the IT industries have their focus on the security of data either stored on the server system or transmitted on wireless media. The objective of proposed work is to utilize the samples of carrier object so that data Hiding capacity a carrier should be maximized without changing samples the carrier. It also focuses on optimizing utilization of selected samples again and again for data hiding. The main idea of this paper is to concentrate on sample utilization and virtual Data Hiding & extraction. Obtained results from propose concept imply that, with virtual data replacement, there is no change in resultant stego object.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133733072","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640757
Neha Bhujbal, Gaurav Prakash Bavdane
To attract more customers every bank comes up with new offers every day. Due to this a customer is highly likely to get churned if the user gets a better offer at another bank. To survive in this competition, banks need to be updated regarding the offers present in market as well as how much their customers are loyal to their services. Customer demographics and credit card usage details are significant parameters to analyze customer behavior in the banking sector. The selected dataset aligns with these parameters but is highly unbalanced, which may produce skewed results. To tackle this issue, various sampling techniques have been employed to create synthetic samples to balance the training data. Even a single Machine Learning algorithm is capable of predicting churn but ensembles have gained popularity due to their robustness and better performance. Consequently, this research work has been experimented with various ensemble algorithms, which led us to the optimal model that combines the results from three ensembles i.e., Random Forests, Extremely Randomized Trees and Adaboost, to achieve better classification performance than any individual or ensemble algorithm. The results obtained by this model can be utilized by banks to make savvy business decisions and take strategic actions to prevent customer churn.
{"title":"Leveraging the efficiency of Ensembles for Customer Retention","authors":"Neha Bhujbal, Gaurav Prakash Bavdane","doi":"10.1109/I-SMAC52330.2021.9640757","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640757","url":null,"abstract":"To attract more customers every bank comes up with new offers every day. Due to this a customer is highly likely to get churned if the user gets a better offer at another bank. To survive in this competition, banks need to be updated regarding the offers present in market as well as how much their customers are loyal to their services. Customer demographics and credit card usage details are significant parameters to analyze customer behavior in the banking sector. The selected dataset aligns with these parameters but is highly unbalanced, which may produce skewed results. To tackle this issue, various sampling techniques have been employed to create synthetic samples to balance the training data. Even a single Machine Learning algorithm is capable of predicting churn but ensembles have gained popularity due to their robustness and better performance. Consequently, this research work has been experimented with various ensemble algorithms, which led us to the optimal model that combines the results from three ensembles i.e., Random Forests, Extremely Randomized Trees and Adaboost, to achieve better classification performance than any individual or ensemble algorithm. The results obtained by this model can be utilized by banks to make savvy business decisions and take strategic actions to prevent customer churn.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"51 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124180157","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640843
Mounicasri Valavala, Wasim Alhamdani
Database performance is a critical factor in determining the application speed. Database indexing is a well- established technique to reduce the query response time, increasing the application speed. The research follows a qualitative analysis approach and aims to drive index tuning to be a dynamic and automated task using ML. This paper is part of the Automatic Index Tuning series and presents the data collection, analysis, and research findings for the index tuning module. The earlier papers in this series presented a literature review, methodology, and theoretical framework. The current paper explains the qualitative analysis process to standardize the parameters influencing the index tuning decision, paving a new path to make index tuning a dynamic and automated task. In addition, it will throw light on the pros and cons of using Machine Learning (ML) classification for index tuning.
{"title":"A Qualitative Case Study of Relational Database Index Tuning Using Machine Learning","authors":"Mounicasri Valavala, Wasim Alhamdani","doi":"10.1109/I-SMAC52330.2021.9640843","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640843","url":null,"abstract":"Database performance is a critical factor in determining the application speed. Database indexing is a well- established technique to reduce the query response time, increasing the application speed. The research follows a qualitative analysis approach and aims to drive index tuning to be a dynamic and automated task using ML. This paper is part of the Automatic Index Tuning series and presents the data collection, analysis, and research findings for the index tuning module. The earlier papers in this series presented a literature review, methodology, and theoretical framework. The current paper explains the qualitative analysis process to standardize the parameters influencing the index tuning decision, paving a new path to make index tuning a dynamic and automated task. In addition, it will throw light on the pros and cons of using Machine Learning (ML) classification for index tuning.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117270695","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640975
T. Venkat Narayana Rao, Gadige Vishal Sai, Panyala Harsha Vardhan Reddy, Sai Harsha Bandarupally, Chukka Nikhil
Over 18 million people die due to Cardio-Vascular Diseases (CVDs), making it the disease that causes more deaths in a human being than other conditions, as stated by a report given by the World Health Organization. However, it is also observed that immediate assistance from a doctor can prevent a curious portion of these deaths by reacting quickly and taking immediate help from a doctor. So, there is a need for a proper mechanism to provide immediate emergency notifications to the hospital management. A new phase of technology has been significantly increasing in recent years, known as Smart Technology, comprising various hardware equipment like sensors, cameras, and modern technologies like AI, ML, IoT, etc. This paper provides an automated, effective solution to notify the hospital management in case of an untimely emergency caused by rapid changes in the individual’s resting heart rate using a smart device that works on IoT, ML, and heartbeat sensors.
{"title":"SHANE – Smart HeartRate Analysis and Notification System for Emergencies","authors":"T. Venkat Narayana Rao, Gadige Vishal Sai, Panyala Harsha Vardhan Reddy, Sai Harsha Bandarupally, Chukka Nikhil","doi":"10.1109/I-SMAC52330.2021.9640975","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640975","url":null,"abstract":"Over 18 million people die due to Cardio-Vascular Diseases (CVDs), making it the disease that causes more deaths in a human being than other conditions, as stated by a report given by the World Health Organization. However, it is also observed that immediate assistance from a doctor can prevent a curious portion of these deaths by reacting quickly and taking immediate help from a doctor. So, there is a need for a proper mechanism to provide immediate emergency notifications to the hospital management. A new phase of technology has been significantly increasing in recent years, known as Smart Technology, comprising various hardware equipment like sensors, cameras, and modern technologies like AI, ML, IoT, etc. This paper provides an automated, effective solution to notify the hospital management in case of an untimely emergency caused by rapid changes in the individual’s resting heart rate using a smart device that works on IoT, ML, and heartbeat sensors.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"8 Suppl 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123676052","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640632
P. Mounika, S. G. Rao
Parkinson’s disease (PD) is a complex condition that is characterized by restricted mobility. Symptoms begin gradually, with only one hand exhibiting a minor tremor on occasion. Also, in the beginning stages of Parkinson's disease, your face may be expressionless. The fingers are not going to vibrate. Your voice may also become mute or slurred. Parkinson's disease indications and symptoms worsen with time. The focus of this thesis is to assess the efficacy of deep learning and machine learning strategies in discovering the best and most accurate strategy for early Parkinson's disease diagnosis utilising a vast dataset from the UCI machine learning repository of 5876 × 22 fields, which includes Parkinson's and healthy people details. Performance analysis of each method is done by considering the metrics like Precision, Recall, F1-Score, Support, Confusion Matrix, Specificity and Sensitivity and are plotted in graph showing training loss and accuracy. The highest accuracy of 97.43% is achieved for KNN with k=5 (K-Nearest Neighbors) algorithm which is a supervised machine learning approach.
{"title":"Machine Learning and Deep Learning Models for Diagnosis of Parkinson’s Disease: A Performance Analysis","authors":"P. Mounika, S. G. Rao","doi":"10.1109/I-SMAC52330.2021.9640632","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640632","url":null,"abstract":"Parkinson’s disease (PD) is a complex condition that is characterized by restricted mobility. Symptoms begin gradually, with only one hand exhibiting a minor tremor on occasion. Also, in the beginning stages of Parkinson's disease, your face may be expressionless. The fingers are not going to vibrate. Your voice may also become mute or slurred. Parkinson's disease indications and symptoms worsen with time. The focus of this thesis is to assess the efficacy of deep learning and machine learning strategies in discovering the best and most accurate strategy for early Parkinson's disease diagnosis utilising a vast dataset from the UCI machine learning repository of 5876 × 22 fields, which includes Parkinson's and healthy people details. Performance analysis of each method is done by considering the metrics like Precision, Recall, F1-Score, Support, Confusion Matrix, Specificity and Sensitivity and are plotted in graph showing training loss and accuracy. The highest accuracy of 97.43% is achieved for KNN with k=5 (K-Nearest Neighbors) algorithm which is a supervised machine learning approach.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122012725","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9641011
Neeraja R, L. Anbarasi
Accurate identification of landmarks from lateral cephalograms plays an important role in cephalometric analysis. Cephalometrics helps orthodontists, dentists, and maxillofacial surgeons to figure out the anatomical abnormalities and thereby provides optimal treatment planning. As the manual marking procedures are measurement error prone and consumes time, a grand challenge is organized by IEEE to automate the detection of landmarks from cephalometric radiographs in the International Symposium on Biomedical Imaging (ISBI) 2014 and 2015. This paper presents a review and comparison for various Artificial Intelligence Techniques proposed to automate cephalometric landmark identification from x-ray images.
{"title":"A Review on Automatic Cephalometric Landmark Identification Using Artificial Intelligence Techniques","authors":"Neeraja R, L. Anbarasi","doi":"10.1109/I-SMAC52330.2021.9641011","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9641011","url":null,"abstract":"Accurate identification of landmarks from lateral cephalograms plays an important role in cephalometric analysis. Cephalometrics helps orthodontists, dentists, and maxillofacial surgeons to figure out the anatomical abnormalities and thereby provides optimal treatment planning. As the manual marking procedures are measurement error prone and consumes time, a grand challenge is organized by IEEE to automate the detection of landmarks from cephalometric radiographs in the International Symposium on Biomedical Imaging (ISBI) 2014 and 2015. This paper presents a review and comparison for various Artificial Intelligence Techniques proposed to automate cephalometric landmark identification from x-ray images.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122176802","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640864
Ming Yan
In the era of rapid development of science and technology, the theory of interior space design is constantly enriched and improved, and the design methods are gradually diversified. Light environment design is an important part of interior space besides color, material and other elements. In this paper, the concept of perceptual representation of knowledge in virtual reality is proposed and discussed in depth. In terms of theoretical framework, this paper analyzes the practical requirements and theoretical basis for the construction of knowledge perception representation theory, and on this basis, the concept of knowledge perception representation is defined.
{"title":"Application of Virtual Reality Technology in Contemporary Environmental Design","authors":"Ming Yan","doi":"10.1109/I-SMAC52330.2021.9640864","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640864","url":null,"abstract":"In the era of rapid development of science and technology, the theory of interior space design is constantly enriched and improved, and the design methods are gradually diversified. Light environment design is an important part of interior space besides color, material and other elements. In this paper, the concept of perceptual representation of knowledge in virtual reality is proposed and discussed in depth. In terms of theoretical framework, this paper analyzes the practical requirements and theoretical basis for the construction of knowledge perception representation theory, and on this basis, the concept of knowledge perception representation is defined.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"9 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120822812","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640956
Atul Kumar Uttam
Corona virus Disease (COVID-2019) spread fast throughout the world, has infected millions of persons, and caused many fatalities. Mobilization has begun throughout the world for this pandemic that is still in existence, with certain constraints and measures being taken to keep this illness from spreading. Furthermore, to manage the illness, affected persons should be found. However, because of the inefficient amount of RT-PCR testing, chest computed tomography (CT) is a common means of supporting COVID-19 diagnosis. The notion of transfer learning was used in this work to detect the covid-19 from the X-ray pictures of the human body chest. With a total accuracy of 92% of the entire model, our model gives the identification of the Covid-19, 96% accuracy. The EfficientNet model previously trained on the Image-Net dataset is used in this study. This research study has customized the changes to the pre-trained model to fit our study and also added a pair of dense and dropout layers before the output layer.
{"title":"Transfer Learning-Based Approach for Identification of COVID-19","authors":"Atul Kumar Uttam","doi":"10.1109/I-SMAC52330.2021.9640956","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640956","url":null,"abstract":"Corona virus Disease (COVID-2019) spread fast throughout the world, has infected millions of persons, and caused many fatalities. Mobilization has begun throughout the world for this pandemic that is still in existence, with certain constraints and measures being taken to keep this illness from spreading. Furthermore, to manage the illness, affected persons should be found. However, because of the inefficient amount of RT-PCR testing, chest computed tomography (CT) is a common means of supporting COVID-19 diagnosis. The notion of transfer learning was used in this work to detect the covid-19 from the X-ray pictures of the human body chest. With a total accuracy of 92% of the entire model, our model gives the identification of the Covid-19, 96% accuracy. The EfficientNet model previously trained on the Image-Net dataset is used in this study. This research study has customized the changes to the pre-trained model to fit our study and also added a pair of dense and dropout layers before the output layer.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126185379","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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