Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276941
K. J. Kumar, R. Sudhir Kumar, V. Nandakumar
The aim of this paper to check the voltage and frequency response of three phase solar PV grid tie string inverter during low voltage ride through. The LVRT performance of an inverter is being checked by its compliance to Central Electricity Authority (CEA), India guidelines, 2019 for grid tie equipment. The study shows that the voltage of the inverter follows the grid with LVRT but in case of frequency, small transients were observed. Similarly, the voltage harmonics generated by the inverter is within the limit throughout the curve but exceeds 5% during the transition from 100% to 15% voltage level.
{"title":"Voltage and frequency response of three phase grid tie solar inverter during LVRT","authors":"K. J. Kumar, R. Sudhir Kumar, V. Nandakumar","doi":"10.1109/ICSTCEE49637.2020.9276941","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276941","url":null,"abstract":"The aim of this paper to check the voltage and frequency response of three phase solar PV grid tie string inverter during low voltage ride through. The LVRT performance of an inverter is being checked by its compliance to Central Electricity Authority (CEA), India guidelines, 2019 for grid tie equipment. The study shows that the voltage of the inverter follows the grid with LVRT but in case of frequency, small transients were observed. Similarly, the voltage harmonics generated by the inverter is within the limit throughout the curve but exceeds 5% during the transition from 100% to 15% voltage level.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115137510","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277501
Jobin Thomas, T. Thivakaran
Schizophrenia is a severe psychiatric condition marked by multiple symptoms, including perceptions, delusions and cognitive problems. Often, schizophrenia may difficult to identify because there is no diagnostic examination yet to identify it. Throughout recent years, machine learning methods have been widely extended to the study of neuroimaging evidence to better identify such disorders. The objective of this paper is to provide a systematic investigation of data mining techniques in Mental Health literature and provide research inputs for schizophrenia. We have investigated on all possible techniques applied in the research of Schizophrenia and concerns to be considered in future works. This review explains challenging research opportunities. Researches based on symptoms/external factors and data sets used are also given importance in this article.
{"title":"Data Mining Algorithms and Statistical Techniques for Identification of Schizophrenia: A Survey","authors":"Jobin Thomas, T. Thivakaran","doi":"10.1109/ICSTCEE49637.2020.9277501","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277501","url":null,"abstract":"Schizophrenia is a severe psychiatric condition marked by multiple symptoms, including perceptions, delusions and cognitive problems. Often, schizophrenia may difficult to identify because there is no diagnostic examination yet to identify it. Throughout recent years, machine learning methods have been widely extended to the study of neuroimaging evidence to better identify such disorders. The objective of this paper is to provide a systematic investigation of data mining techniques in Mental Health literature and provide research inputs for schizophrenia. We have investigated on all possible techniques applied in the research of Schizophrenia and concerns to be considered in future works. This review explains challenging research opportunities. Researches based on symptoms/external factors and data sets used are also given importance in this article.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123413568","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277222
P. Gupta, Saurabh H. Deshmukh, S. Pandey, Kedar Tonge, Vrushabh Urkunde, Sainath Kide
Industry 4.0 might be thumping at our door, but there are millions of individuals who are still disconnected from even the most fundamental technologies. One of the major reasons for this disparity is the language gap. The majority of them don't know English, which is the de-facto language for most of the technologies. Only 12.6% of all Indians speak English according to the 2011 census. Language is the medium through which an individual expresses himself or herself. Education of the rural section of society is one of the most important things to accomplish if we aim to develop the country. Because of this, there is a need for a reliable software solution for recognizing the traditional scripts. This would also be helpful for the purpose of remote schooling in times of lockdown and quarantine.The paper proposes a methodology for recognition of handwritten ‘Devanagari’ characters. Devanagari being one of the most common scripts, is used in many Indian dialects. The Hindi language is also written in the Devanagari script as shown in Fig 1. This paper explores and analyzes the use of Deep learning techniques such as the Convolutional Neural Networks for the recognition of Devanagari characters. Inspired by the structure of the brain, CNNs classify characters by making use of neurons linked in various layers so as to achieve maximum efficiency. In this paper, 6 layers of neurons were used for the purpose of classifying Devanagari characters. An accuracy of 95.6% was achieved in this approach. Once recognized, the handwritten Devanagari characters can easily be translated into English or any other languages.
{"title":"Convolutional Neural Network based Handwritten Devanagari Character Recognition","authors":"P. Gupta, Saurabh H. Deshmukh, S. Pandey, Kedar Tonge, Vrushabh Urkunde, Sainath Kide","doi":"10.1109/ICSTCEE49637.2020.9277222","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277222","url":null,"abstract":"Industry 4.0 might be thumping at our door, but there are millions of individuals who are still disconnected from even the most fundamental technologies. One of the major reasons for this disparity is the language gap. The majority of them don't know English, which is the de-facto language for most of the technologies. Only 12.6% of all Indians speak English according to the 2011 census. Language is the medium through which an individual expresses himself or herself. Education of the rural section of society is one of the most important things to accomplish if we aim to develop the country. Because of this, there is a need for a reliable software solution for recognizing the traditional scripts. This would also be helpful for the purpose of remote schooling in times of lockdown and quarantine.The paper proposes a methodology for recognition of handwritten ‘Devanagari’ characters. Devanagari being one of the most common scripts, is used in many Indian dialects. The Hindi language is also written in the Devanagari script as shown in Fig 1. This paper explores and analyzes the use of Deep learning techniques such as the Convolutional Neural Networks for the recognition of Devanagari characters. Inspired by the structure of the brain, CNNs classify characters by making use of neurons linked in various layers so as to achieve maximum efficiency. In this paper, 6 layers of neurons were used for the purpose of classifying Devanagari characters. An accuracy of 95.6% was achieved in this approach. Once recognized, the handwritten Devanagari characters can easily be translated into English or any other languages.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126715777","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277130
Pratyush Panda, Adithya Ballaji, Sujo Oommen, Manish Bharat
Weather conditions become an extremely important parameter before the outset of major constructional projects at remote places. This paper proposes the design and development of weather station which is powered by utilizing renewable energy for such remote places where there is no electricity supply and has been developed for unmanned operations which would continuously render real time weather related data using Internet of Things i.e., IoT to provide graphical data of the weather conditions over a long period of time. The proposed device will measure weather parameters such as temperature, humidity, pressure, altitude and pollution levels with high precision and at very less power consumption to provide all the round 24 hours of active operation.
{"title":"Weather Parameter and Pollution Level Extraction using IoT for Various Traffic Nodal Points with Solar Charging","authors":"Pratyush Panda, Adithya Ballaji, Sujo Oommen, Manish Bharat","doi":"10.1109/ICSTCEE49637.2020.9277130","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277130","url":null,"abstract":"Weather conditions become an extremely important parameter before the outset of major constructional projects at remote places. This paper proposes the design and development of weather station which is powered by utilizing renewable energy for such remote places where there is no electricity supply and has been developed for unmanned operations which would continuously render real time weather related data using Internet of Things i.e., IoT to provide graphical data of the weather conditions over a long period of time. The proposed device will measure weather parameters such as temperature, humidity, pressure, altitude and pollution levels with high precision and at very less power consumption to provide all the round 24 hours of active operation.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124601332","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277006
H. Khatoon, Dipti Verma, Ankit Arora
Diabetes among one of the most common diseases occurs in human beings due to imbalance of insulin level in blood. The early detection of diabetes is very necessary as it can affect many internal parts and immune system of human body silently. In this paper, we are comparing various machine learning and neural network based approaches that are applied on publically available datasets. Here, we have used two datasets for experiments 1st dataset is UCI dataset and other is PIMA Indian dataset then we have performed lots of experiments using different machine learning classifiers and neural network models to observe the performance of each classifier. After experiments, the highest accuracy of identification obtained from decision tree method which is 99.8% for dataset1 and for dataset 2 the highest accuracy was obtained from back propagation neural network model which is 80.8 %.
{"title":"Identification of Diabetes Disease from Human Blood Using Machine Learning Techniques","authors":"H. Khatoon, Dipti Verma, Ankit Arora","doi":"10.1109/ICSTCEE49637.2020.9277006","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277006","url":null,"abstract":"Diabetes among one of the most common diseases occurs in human beings due to imbalance of insulin level in blood. The early detection of diabetes is very necessary as it can affect many internal parts and immune system of human body silently. In this paper, we are comparing various machine learning and neural network based approaches that are applied on publically available datasets. Here, we have used two datasets for experiments 1st dataset is UCI dataset and other is PIMA Indian dataset then we have performed lots of experiments using different machine learning classifiers and neural network models to observe the performance of each classifier. After experiments, the highest accuracy of identification obtained from decision tree method which is 99.8% for dataset1 and for dataset 2 the highest accuracy was obtained from back propagation neural network model which is 80.8 %.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124645691","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276948
S. Banu, S. Patil
Chatbot is an Artificial Intelligence program that stimulates interactive human conversations with computers. It plays a vital role now-a days due to its 24/7 support for customer queries. Web app chatbot uses a Linguistic machine learning algorithm (NLP) for predicting correct responses for human queries. LUIS (Language Understanding Intelligent Service) is a natural Language processing Artificial Intelligence for predicting human queries. In this paper, chatbot is implemented on LUIS for predicting the user queries. Based on the highest prediction score, Luis detects the intents and entities, to solve user queries. A web app chatbot discussed in this paper is fast, accurate and secure with high performance. Using LUIS API’s for automated LUIS training and publishing the endpoint to the chatbot. Enhanced authentication secures the bot from unauthorized persons accessing the chatbot.
{"title":"An Intelligent Web App Chatbot","authors":"S. Banu, S. Patil","doi":"10.1109/ICSTCEE49637.2020.9276948","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276948","url":null,"abstract":"Chatbot is an Artificial Intelligence program that stimulates interactive human conversations with computers. It plays a vital role now-a days due to its 24/7 support for customer queries. Web app chatbot uses a Linguistic machine learning algorithm (NLP) for predicting correct responses for human queries. LUIS (Language Understanding Intelligent Service) is a natural Language processing Artificial Intelligence for predicting human queries. In this paper, chatbot is implemented on LUIS for predicting the user queries. Based on the highest prediction score, Luis detects the intents and entities, to solve user queries. A web app chatbot discussed in this paper is fast, accurate and secure with high performance. Using LUIS API’s for automated LUIS training and publishing the endpoint to the chatbot. Enhanced authentication secures the bot from unauthorized persons accessing the chatbot.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124703268","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277420
P. Chary, T. Mahesh, A. N. Kumar, K. Lingaswamy, T. Babu, B. Navothna
The radial network travels over the network without being linked to any other supply. It is used for loads such as rural areas. Load-flow studies are carried out with ETAP (14.0) software which simulates current operating conditions for the steady-state system that allows an assessment of bus voltage profiles, actual and reactive power flow and losses. The load-flow analysis conducted using various scenarios ensures that the power system is correctly designed to meet the performance requirements. The benefits of the electricity flow study decrease unforeseen downtimes, minimal operational and maintenance costs and obtain more capacity from existing assets. The main purpose of this study is to develop a new load-flow technology for all network nodes without that the network.
{"title":"Load Flow Analysis of Radial Distribution System","authors":"P. Chary, T. Mahesh, A. N. Kumar, K. Lingaswamy, T. Babu, B. Navothna","doi":"10.1109/ICSTCEE49637.2020.9277420","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277420","url":null,"abstract":"The radial network travels over the network without being linked to any other supply. It is used for loads such as rural areas. Load-flow studies are carried out with ETAP (14.0) software which simulates current operating conditions for the steady-state system that allows an assessment of bus voltage profiles, actual and reactive power flow and losses. The load-flow analysis conducted using various scenarios ensures that the power system is correctly designed to meet the performance requirements. The benefits of the electricity flow study decrease unforeseen downtimes, minimal operational and maintenance costs and obtain more capacity from existing assets. The main purpose of this study is to develop a new load-flow technology for all network nodes without that the network.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127664201","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277293
Sundeep. Siddula, Ch. Dennis Gleeson, P. Geetha kumari
The research on power generation renewable energy sources are increasing In this paper the proposing automatic position control system of solar panel is introduced as the position of sun is changing through out the day, in order to maximize the generation I.e, maximizing the conversion of solar energy to electrical energy. The solar panel has to be faced towards the sun in order to get maximum solar energy. The LDR (light dependent resistors) is used as the sensor to detect the intensity of sunlight. And the main heart of this project is arduino Uno, where all the processing is done to know the position of the sun. Servo motor is used to move the solar panel based on signal received from arduino. This system is eco-friendly and is operating at low-cost. Finally the result will show the effectiveness of this system when compared to regular solar system.
{"title":"Solar Panel Position Control and Monitoring System For Maximum Power Generation","authors":"Sundeep. Siddula, Ch. Dennis Gleeson, P. Geetha kumari","doi":"10.1109/ICSTCEE49637.2020.9277293","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277293","url":null,"abstract":"The research on power generation renewable energy sources are increasing In this paper the proposing automatic position control system of solar panel is introduced as the position of sun is changing through out the day, in order to maximize the generation I.e, maximizing the conversion of solar energy to electrical energy. The solar panel has to be faced towards the sun in order to get maximum solar energy. The LDR (light dependent resistors) is used as the sensor to detect the intensity of sunlight. And the main heart of this project is arduino Uno, where all the processing is done to know the position of the sun. Servo motor is used to move the solar panel based on signal received from arduino. This system is eco-friendly and is operating at low-cost. Finally the result will show the effectiveness of this system when compared to regular solar system.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133050601","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277477
Rishav Dubey, Srikar Chaganti, P. Ananthakumar
Electric Vehicle is anticipated to have a massive market soon in our country. This accounts for having a better performance of the vehicle. Hence estimating the performance and behavior of the Electric Vehicle components reduces testing time and cost and makes it more efficient. This paper deals with the modeling and simulation of the electric drive system of an electric vehicle on Matlab/Simulink. The system gives various performance parameters of the electric motor and the battery pack by taking speed and torque as the input. Field oriented control method is used for motor modeling. Constant current value drawn by the PMSM motor is fed into the Li-ion battery pack, and its behavior is studied.
{"title":"Modeling and Simulation of Powertrain of an Electric Vehicle","authors":"Rishav Dubey, Srikar Chaganti, P. Ananthakumar","doi":"10.1109/ICSTCEE49637.2020.9277477","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277477","url":null,"abstract":"Electric Vehicle is anticipated to have a massive market soon in our country. This accounts for having a better performance of the vehicle. Hence estimating the performance and behavior of the Electric Vehicle components reduces testing time and cost and makes it more efficient. This paper deals with the modeling and simulation of the electric drive system of an electric vehicle on Matlab/Simulink. The system gives various performance parameters of the electric motor and the battery pack by taking speed and torque as the input. Field oriented control method is used for motor modeling. Constant current value drawn by the PMSM motor is fed into the Li-ion battery pack, and its behavior is studied.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133545767","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277379
Sandeep Kumar, K. Prasad, A. Srilekha, T. Suman, B. Rao, J. V. Vamshi Krishna
Detection of diseases in plants is a significant task that has to be done in agriculture. This is something on which the economy profoundly depends. Infection discovery in plants is a significant job in the agribusiness field, as having diseases in plants is very common. To recognize the diseases in leaves, a continuous observation of the plants is required. This observation or continuous monitoring of the plants takes a lot of human effort and it is time-consuming too. To make it simply some sort of programmed strategy is required to observe the plants. Program based identification of diseases in plants makes easier to detect the damaged leaves and reduces human efforts and time-saving. The proposed algorithm distinguishing sickness in plants and classify them more accurately as compared to existing techniques.
{"title":"Leaf Disease Detection and Classification based on Machine Learning","authors":"Sandeep Kumar, K. Prasad, A. Srilekha, T. Suman, B. Rao, J. V. Vamshi Krishna","doi":"10.1109/ICSTCEE49637.2020.9277379","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277379","url":null,"abstract":"Detection of diseases in plants is a significant task that has to be done in agriculture. This is something on which the economy profoundly depends. Infection discovery in plants is a significant job in the agribusiness field, as having diseases in plants is very common. To recognize the diseases in leaves, a continuous observation of the plants is required. This observation or continuous monitoring of the plants takes a lot of human effort and it is time-consuming too. To make it simply some sort of programmed strategy is required to observe the plants. Program based identification of diseases in plants makes easier to detect the damaged leaves and reduces human efforts and time-saving. The proposed algorithm distinguishing sickness in plants and classify them more accurately as compared to existing techniques.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133350649","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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