Pub Date : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399599
N. Sharma, Pratima Verma, Vimal Kumar, Ramkumar Arunachalam
The entire human life is passing through a very bad and unprecedented phase of the pandemic called COVID- 19. It is a chronic disease that occurs because of “severe acute respiratory syndrome coronavirus 2 (SARS-Co V-2)”. The entire world has witnessed a very bad phase of life which has never happened before on this massive scale. COVID-19 has made the entire human life challenging. Millions of people got affected around the globe and many lost their loving ones while fighting with the deadly disease. The two critical challenges of the pandemic are: there are no known treatments for COVID-19 and secondly, its transmission from one person to another is very prompt. Therefore, to control the deadly spread of the pandemic the countries have adopted complete lockdown for months, people were isolated and quarantined to control the spread of the disease. Several terminologies such as lockdown, quarantine, social-distancing, home isolation, and Corona waves can be heard around. In all these necessary measures to control the virus taken by the government the entire humankind suffered and still suffering from several challenges towards living a normal life. In this entire disaster, information communication technologies (ICTs) have shown a significant contribution in mitigating the effects and challenges caused due to COVID-19. In the present study, efforts have been given on highlighting the role of ICT in overcoming the challenges of life caused due to COVID-19 with the help of studies that took place in the pandemic duration. The study has also shown that how the extensive inclination of the people towards the use of ICTs helped in emerging new business opportunities. The present study is a conceptual study that will help in leading to another study. A research model has been proposed in the study which can be further tested in upcoming studies. The outcomes of the study can be helpful for the decision and policymakers especially those who are working in the area of ICT. The ICT industry can learn many things that can help focus more on the expansion of business opportunities.
{"title":"ICT in Mitigating Challenges of Life Amid COVID-19 and Emerging Business Opportunities","authors":"N. Sharma, Pratima Verma, Vimal Kumar, Ramkumar Arunachalam","doi":"10.1109/ICITIIT51526.2021.9399599","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399599","url":null,"abstract":"The entire human life is passing through a very bad and unprecedented phase of the pandemic called COVID- 19. It is a chronic disease that occurs because of “severe acute respiratory syndrome coronavirus 2 (SARS-Co V-2)”. The entire world has witnessed a very bad phase of life which has never happened before on this massive scale. COVID-19 has made the entire human life challenging. Millions of people got affected around the globe and many lost their loving ones while fighting with the deadly disease. The two critical challenges of the pandemic are: there are no known treatments for COVID-19 and secondly, its transmission from one person to another is very prompt. Therefore, to control the deadly spread of the pandemic the countries have adopted complete lockdown for months, people were isolated and quarantined to control the spread of the disease. Several terminologies such as lockdown, quarantine, social-distancing, home isolation, and Corona waves can be heard around. In all these necessary measures to control the virus taken by the government the entire humankind suffered and still suffering from several challenges towards living a normal life. In this entire disaster, information communication technologies (ICTs) have shown a significant contribution in mitigating the effects and challenges caused due to COVID-19. In the present study, efforts have been given on highlighting the role of ICT in overcoming the challenges of life caused due to COVID-19 with the help of studies that took place in the pandemic duration. The study has also shown that how the extensive inclination of the people towards the use of ICTs helped in emerging new business opportunities. The present study is a conceptual study that will help in leading to another study. A research model has been proposed in the study which can be further tested in upcoming studies. The outcomes of the study can be helpful for the decision and policymakers especially those who are working in the area of ICT. The ICT industry can learn many things that can help focus more on the expansion of business opportunities.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115003922","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399592
Arsal Imtiaz, S. Nachiket, K. Nishanth, J. Angadi, T. C. Pramod
Agricultural loans provide a much-needed support structure for the overall functioning of the agricultural industry in a country like India where a majority of farmland is owned by a multitude of people, which leads to scattered ownership of the overall farmland and in turn restricts the potential growth of the agricultural industry. This leads to the need for a proper system to improve the efficiency of loan acquisition on the farmer's end and loan supply on the bank's end. In this paper, a feasible Agricultural Loan Recommender system is presented using K- nearest neighbour algorithm. It enables the farmers to look up statistical and graphical data relevant to agricultural loans and to get recommendations for said loans. Using this system can help farmers be better informed on the overall process of the loan application as well as which bank would be the most suitable to apply for a loan based on their needs. The results of the scheme are analysed with respect to the probability of bank recommendation based on the requested loan amount.
{"title":"Agricultural Loan Recommender System - A Machine Learning Approach","authors":"Arsal Imtiaz, S. Nachiket, K. Nishanth, J. Angadi, T. C. Pramod","doi":"10.1109/ICITIIT51526.2021.9399592","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399592","url":null,"abstract":"Agricultural loans provide a much-needed support structure for the overall functioning of the agricultural industry in a country like India where a majority of farmland is owned by a multitude of people, which leads to scattered ownership of the overall farmland and in turn restricts the potential growth of the agricultural industry. This leads to the need for a proper system to improve the efficiency of loan acquisition on the farmer's end and loan supply on the bank's end. In this paper, a feasible Agricultural Loan Recommender system is presented using K- nearest neighbour algorithm. It enables the farmers to look up statistical and graphical data relevant to agricultural loans and to get recommendations for said loans. Using this system can help farmers be better informed on the overall process of the loan application as well as which bank would be the most suitable to apply for a loan based on their needs. The results of the scheme are analysed with respect to the probability of bank recommendation based on the requested loan amount.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116562685","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}
In today's world, mental illness has become a common problem in several individuals life still, the diagnosis of mental disorders relies on traditional methods of testing by interpreting the patient just by psychometric test and by not taking into consideration various other factors. Whilst the number of social media users and smartwatch users have increased rapidly, software applications that interpret psychological data for health-related decisions have not followed a similar trend. The main motive behind this study is to examine the sentiments of the user's social media data and detect unusual patterns by smartwatch data analytics to help mental health workers in decision making. The paper proposes the methodology to capture and analyze real-time data of smartwatch and social media.
{"title":"Use of Social Media and Smartwatch Data Analytics for Mental Health Diagnosis","authors":"Nakul Amate, Sagarika Patil, Pranav Jojan, Sahil Morankar","doi":"10.1109/ICITIIT51526.2021.9399591","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399591","url":null,"abstract":"In today's world, mental illness has become a common problem in several individuals life still, the diagnosis of mental disorders relies on traditional methods of testing by interpreting the patient just by psychometric test and by not taking into consideration various other factors. Whilst the number of social media users and smartwatch users have increased rapidly, software applications that interpret psychological data for health-related decisions have not followed a similar trend. The main motive behind this study is to examine the sentiments of the user's social media data and detect unusual patterns by smartwatch data analytics to help mental health workers in decision making. The paper proposes the methodology to capture and analyze real-time data of smartwatch and social media.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122887189","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399589
Varindra Kumar
The paper proposes an economical, small size and compact fractal Koch dipole antenna for its resonance within 4 - 5 GHz frequency band. The antenna and its array have been bent to calculate and show the parametric behavior with its curvature. The reflection parameter and its gain within the frequency band has also been calculated and compared with open end, short end and its bend configuration. A trained neural network function has been used to calculate antenna parameters of the array antenna using the known parameters of single element antenna. In addition the paper also provides frequency dependent impedance plot using ADS tool and its matching circuit for its application within controlled impedance PCB environment.
{"title":"Neural Network analysis of Fractal Koch Antenna","authors":"Varindra Kumar","doi":"10.1109/ICITIIT51526.2021.9399589","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399589","url":null,"abstract":"The paper proposes an economical, small size and compact fractal Koch dipole antenna for its resonance within 4 - 5 GHz frequency band. The antenna and its array have been bent to calculate and show the parametric behavior with its curvature. The reflection parameter and its gain within the frequency band has also been calculated and compared with open end, short end and its bend configuration. A trained neural network function has been used to calculate antenna parameters of the array antenna using the known parameters of single element antenna. In addition the paper also provides frequency dependent impedance plot using ADS tool and its matching circuit for its application within controlled impedance PCB environment.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127728923","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399598
N. V. Choudhari, Ashish B. Sasankar
The GI (Govt. of India) cloud started in 2014 is built on the state of art technologies and rich architecture with the nationwide network infrastructure and Data Centres located across the country on National and State data centres. This paper investigates, study and analyze the cloud architecture of Govt. of India and suggests modifications that need to be adapted for sustainable development as per the global changing scenario and fulfill the future needs with improved service delivery, increased throughput, and increased efficiency to provide secured cloud services and to minimize the gap between the cloud service providers and end-users. The cloud services are designed for centralized storage and processing. The cloud data centers are generally located thousands of miles away from the end-users where the data is actually generated. The physical distance between the cloud infrastructure and the data source at edge level end-users produces latency for the real-time processing of the huge amount of data generated at the source level. In recent years the automation scenario is changing globally with various emerging technologies such as the Internet of Things (IoT), Wireless Fidelity 6 (Wi-Fi 6), Fifth Generation Mobile Network connectivity (5G), Artificial Intelligence (AI), and Machine Learning, etc. Emerging technologies like IoT, Wi-Fi 6, 5G gives large scope for boundary level computing and generates a very huge amount of data at the data source level produced by the end-users. These technologies require agile real-time processing and analysis of the data at the source level. Edge computing and Fog computing are the distributed architectures that work together, for reduced latency and speedy real-time processing where the data is actually generated by the end-user. According to the new implementation demands, various emerging cloud technologies such as Mobile Cloud Apps, Containers, Serverless, Microservices, Development and Information Technology Operations (DevOps), BlockChain, Fog computing, Edge Computing, and Software-Defined Infrastructure (SDI), etc are proposed for implementation
{"title":"Architectural Vision of Cloud Computing in the Indian Government","authors":"N. V. Choudhari, Ashish B. Sasankar","doi":"10.1109/ICITIIT51526.2021.9399598","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399598","url":null,"abstract":"The GI (Govt. of India) cloud started in 2014 is built on the state of art technologies and rich architecture with the nationwide network infrastructure and Data Centres located across the country on National and State data centres. This paper investigates, study and analyze the cloud architecture of Govt. of India and suggests modifications that need to be adapted for sustainable development as per the global changing scenario and fulfill the future needs with improved service delivery, increased throughput, and increased efficiency to provide secured cloud services and to minimize the gap between the cloud service providers and end-users. The cloud services are designed for centralized storage and processing. The cloud data centers are generally located thousands of miles away from the end-users where the data is actually generated. The physical distance between the cloud infrastructure and the data source at edge level end-users produces latency for the real-time processing of the huge amount of data generated at the source level. In recent years the automation scenario is changing globally with various emerging technologies such as the Internet of Things (IoT), Wireless Fidelity 6 (Wi-Fi 6), Fifth Generation Mobile Network connectivity (5G), Artificial Intelligence (AI), and Machine Learning, etc. Emerging technologies like IoT, Wi-Fi 6, 5G gives large scope for boundary level computing and generates a very huge amount of data at the data source level produced by the end-users. These technologies require agile real-time processing and analysis of the data at the source level. Edge computing and Fog computing are the distributed architectures that work together, for reduced latency and speedy real-time processing where the data is actually generated by the end-user. According to the new implementation demands, various emerging cloud technologies such as Mobile Cloud Apps, Containers, Serverless, Microservices, Development and Information Technology Operations (DevOps), BlockChain, Fog computing, Edge Computing, and Software-Defined Infrastructure (SDI), etc are proposed for implementation","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114190813","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399610
Vihaan Nama, Vinay V. Hegde, B. S. Satish Babu
Movie reviews are vital in telling the viewer whether a movie is worth watching or not. They can be classified into textual and non-textual movie reviews. While non-textual movie reviews (stars) give the user information as to how the movie fairs, textual movie reviews give the user a more detailed picture on the positive and negative aspects of the movie. Sentiment Analysis is the use of natural language processing, text analysis, biometrics and computational linguistics to identify, quantify, extract and effectively study states and subjective information given in textual format. This paper aims to conduct sentiment analysis of reviews of movies by using the Naive-Bayes algorithm and compare the results to that of a Rule-Based Approach using the AFINN-111 sentiment dictionary.
{"title":"Sentiment Analysis of Movie Reviews: A Comparative Study between the Naive-Bayes Classifier and a Rule-based Approach","authors":"Vihaan Nama, Vinay V. Hegde, B. S. Satish Babu","doi":"10.1109/ICITIIT51526.2021.9399610","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399610","url":null,"abstract":"Movie reviews are vital in telling the viewer whether a movie is worth watching or not. They can be classified into textual and non-textual movie reviews. While non-textual movie reviews (stars) give the user information as to how the movie fairs, textual movie reviews give the user a more detailed picture on the positive and negative aspects of the movie. Sentiment Analysis is the use of natural language processing, text analysis, biometrics and computational linguistics to identify, quantify, extract and effectively study states and subjective information given in textual format. This paper aims to conduct sentiment analysis of reviews of movies by using the Naive-Bayes algorithm and compare the results to that of a Rule-Based Approach using the AFINN-111 sentiment dictionary.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126673101","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399602
K. Kavipriya, Manjunatha Hiremath
Coronary Artery supplies oxygenated blood and nutrients to the heart muscles. It can be narrow by the plaque deposited on the artery wall. Cardiologists and radiologists diagnose the disease through visual inspection based on x-ray images. It is a challenging part for them to identify the plaque in the artery in the given imagery. By using image processing and pattern recognition techniques, a narrowed artery can be identified. In this paper, pre-processing methods of image processing are discussed with respect to coronary angiogram image(s). In general the angiogram images are affected by device generated noise / artifacts; pre-processing techniques help to reduce the noise in the image and to enhance the quality of the image so that the region of interest is sensed. The main objective of the medical image analysis is to localize the region of interest by removing the noise. It is essential to find the structure of the artery in the angiogram image, for that preprocessing is useful.
{"title":"Analysis of Benchmark Image Pre-Processing Techniques for Coronary Angiogram Images","authors":"K. Kavipriya, Manjunatha Hiremath","doi":"10.1109/ICITIIT51526.2021.9399602","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399602","url":null,"abstract":"Coronary Artery supplies oxygenated blood and nutrients to the heart muscles. It can be narrow by the plaque deposited on the artery wall. Cardiologists and radiologists diagnose the disease through visual inspection based on x-ray images. It is a challenging part for them to identify the plaque in the artery in the given imagery. By using image processing and pattern recognition techniques, a narrowed artery can be identified. In this paper, pre-processing methods of image processing are discussed with respect to coronary angiogram image(s). In general the angiogram images are affected by device generated noise / artifacts; pre-processing techniques help to reduce the noise in the image and to enhance the quality of the image so that the region of interest is sensed. The main objective of the medical image analysis is to localize the region of interest by removing the noise. It is essential to find the structure of the artery in the angiogram image, for that preprocessing is useful.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130709364","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399594
K. Amrutha, P. Prabu
This paper reviews different steps in an automated sign language recognition (SLR) system. Developing a system that can read and interpret a sign must be trained using a large dataset and the best algorithm. As a basic SLR system, an isolated recognition model is developed. The model is based on vision-based isolated hand gesture detection and recognition. Assessment of ML-based SLR model was conducted with the help of 4 candidates under a controlled environment. The model made use of a convex hull for feature extraction and KNN for classification. The model yielded 65% accuracy.
{"title":"ML Based Sign Language Recognition System","authors":"K. Amrutha, P. Prabu","doi":"10.1109/ICITIIT51526.2021.9399594","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399594","url":null,"abstract":"This paper reviews different steps in an automated sign language recognition (SLR) system. Developing a system that can read and interpret a sign must be trained using a large dataset and the best algorithm. As a basic SLR system, an isolated recognition model is developed. The model is based on vision-based isolated hand gesture detection and recognition. Assessment of ML-based SLR model was conducted with the help of 4 candidates under a controlled environment. The model made use of a convex hull for feature extraction and KNN for classification. The model yielded 65% accuracy.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114885942","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399603
P. S. Shekar Varma, Sushil Kumar, K. Sri Vasuki Reddy
In contemporary years, the categorization of breast cancer has become an engrossing subject in the department of healthcare informatics due to prodigious deaths of the women across the world caused by this cancer. With the upcoming heed and variety of approaches in image processing and machine learning (ML), there has been an endeavor to erect a pattern recognition model that is well-grounded to boost the diagnosis standard. Diverse research has been attempted on mastering the prediction of the possibility of breast cancer using predefined data mining algorithms. In this paper, a model is presented using the support vector machine (SVM) algorithm for the manual categorizing of the histology images of breast cancer samples into benign and malignant subclasses to anticipate the interpretation. Primarily all the data incorporating a set of 30 features relating to the cell nuclei shown in the digitalized images of fine needle aspirate (FNA) of a breast mass are considered. Ten existing values of features are added up for every nuclei sample then the mean, the standard deviation, the worst and largest of the mentioned attributes are measured proceeding to 30 features. The total features obtained are visualized and apprehended to gain insight for future diagnosis. The principal component analysis (PCA) dimensionality reduction strategy is implemented to successfully augment the valiance of the attributes resolving eigenvector problem. The ultimate outcome is conceptualized using the confusion matrix and the receiver operating characteristic curve (ROC). This SVM forged model proves to show 97% accuracy with the recommended dataset.
{"title":"Machine Learning Based Breast Cancer Visualization and Classification","authors":"P. S. Shekar Varma, Sushil Kumar, K. Sri Vasuki Reddy","doi":"10.1109/ICITIIT51526.2021.9399603","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399603","url":null,"abstract":"In contemporary years, the categorization of breast cancer has become an engrossing subject in the department of healthcare informatics due to prodigious deaths of the women across the world caused by this cancer. With the upcoming heed and variety of approaches in image processing and machine learning (ML), there has been an endeavor to erect a pattern recognition model that is well-grounded to boost the diagnosis standard. Diverse research has been attempted on mastering the prediction of the possibility of breast cancer using predefined data mining algorithms. In this paper, a model is presented using the support vector machine (SVM) algorithm for the manual categorizing of the histology images of breast cancer samples into benign and malignant subclasses to anticipate the interpretation. Primarily all the data incorporating a set of 30 features relating to the cell nuclei shown in the digitalized images of fine needle aspirate (FNA) of a breast mass are considered. Ten existing values of features are added up for every nuclei sample then the mean, the standard deviation, the worst and largest of the mentioned attributes are measured proceeding to 30 features. The total features obtained are visualized and apprehended to gain insight for future diagnosis. The principal component analysis (PCA) dimensionality reduction strategy is implemented to successfully augment the valiance of the attributes resolving eigenvector problem. The ultimate outcome is conceptualized using the confusion matrix and the receiver operating characteristic curve (ROC). This SVM forged model proves to show 97% accuracy with the recommended dataset.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114447269","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 : 2021-02-11DOI: 10.1109/ICITIIT51526.2021.9399590
S. E. Warkhede, S. K. Yadav, V. Thakare, P. E. Ajmire
The entirely distinct pattern recognition technologies have been proposed over recent years and thus the different research teams focus on the effects of popularity. Because of its use in many areas, such as pattern recognition and machine learning, handwritten character recognition has found great success. In online handwritten character recognition, the basic field is for use. The various character recognition techniques were suggested in the offline handwritten recognition process. Although the techniques for transforming textual content are established by some empirical studies and publications. This textual material has been translated from a paper file into a machine-readable form. The character recognition system could help produce a paperless document as a key in the coming days. The key aspect was the digitization of paper documents and the retrieval of existing paper records as well. In this job, we took out offline samples of some Rajasthani handwritten characters. The proposed average recognition rate for machine archives is 89.82 percent, using histogram oriented gradient features and support vector machine classifiers.
{"title":"Handwritten Recognition of Rajasthani Characters by Classifier SVM","authors":"S. E. Warkhede, S. K. Yadav, V. Thakare, P. E. Ajmire","doi":"10.1109/ICITIIT51526.2021.9399590","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399590","url":null,"abstract":"The entirely distinct pattern recognition technologies have been proposed over recent years and thus the different research teams focus on the effects of popularity. Because of its use in many areas, such as pattern recognition and machine learning, handwritten character recognition has found great success. In online handwritten character recognition, the basic field is for use. The various character recognition techniques were suggested in the offline handwritten recognition process. Although the techniques for transforming textual content are established by some empirical studies and publications. This textual material has been translated from a paper file into a machine-readable form. The character recognition system could help produce a paperless document as a key in the coming days. The key aspect was the digitization of paper documents and the retrieval of existing paper records as well. In this job, we took out offline samples of some Rajasthani handwritten characters. The proposed average recognition rate for machine archives is 89.82 percent, using histogram oriented gradient features and support vector machine classifiers.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124973136","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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