Pub Date : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200043
Lakshmi Dutta, Dushmanta Kumar Das
This research work develops an explicit nonlinear model predictive control strategy for an aerodynamical model i.e. twin rotor MIMO system (TRMS). Here the control strategy is developed by calculating the tracking error as well as the control signal in the prediction horizon using Taylor series expansion. The explicit solution for the control signal is obtained from an optimal performance index which can be developed without online optimization. The complete state information of the system to the proposed controller is given from an ensemble Kalman filter (EnKF) based state observer. The simulation and real-time results are documented in graphical form to confirm the efficiency of the proposed controller.
{"title":"An Ensemble Kalman Filter based Explicit Nonlinear Model Predictive Control Design for Two Degree Freedom of Helicopter Model","authors":"Lakshmi Dutta, Dushmanta Kumar Das","doi":"10.1109/ComPE49325.2020.9200043","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200043","url":null,"abstract":"This research work develops an explicit nonlinear model predictive control strategy for an aerodynamical model i.e. twin rotor MIMO system (TRMS). Here the control strategy is developed by calculating the tracking error as well as the control signal in the prediction horizon using Taylor series expansion. The explicit solution for the control signal is obtained from an optimal performance index which can be developed without online optimization. The complete state information of the system to the proposed controller is given from an ensemble Kalman filter (EnKF) based state observer. The simulation and real-time results are documented in graphical form to confirm the efficiency of the proposed controller.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"59 1","pages":"033-038"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72892776","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200166
Arpita Nema
The paper proposes "Anti-spoofing application for desktop". This application uses a face recognition approach along with the use of eye-blink count to detect liveness. Main phases of application are namely, face detection and recognition, and determination of liveness status of user. Liveness detection is proven to prevent the video play-back attacks and use of printed photograph in order to compromise the security. Webcam captures the user’s image after every short interval of time. Image captured after passing authentication process is checked for liveness. In case of security breach, countermeasures are executed. This include capturing image of adversary and system logoff or exit. This paper proposes an additional functionality which uses HOG feature descriptor of user image along with passcode. It uses SVM classifier that gives performance metric of 100% accuracy. The experimental results of the ameliorated functionality show the effectiveness of the proposed approach.
{"title":"Ameliorated Anti-Spoofing Application for PCs with Users’ Liveness Detection Using Blink Count","authors":"Arpita Nema","doi":"10.1109/ComPE49325.2020.9200166","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200166","url":null,"abstract":"The paper proposes \"Anti-spoofing application for desktop\". This application uses a face recognition approach along with the use of eye-blink count to detect liveness. Main phases of application are namely, face detection and recognition, and determination of liveness status of user. Liveness detection is proven to prevent the video play-back attacks and use of printed photograph in order to compromise the security. Webcam captures the user’s image after every short interval of time. Image captured after passing authentication process is checked for liveness. In case of security breach, countermeasures are executed. This include capturing image of adversary and system logoff or exit. This paper proposes an additional functionality which uses HOG feature descriptor of user image along with passcode. It uses SVM classifier that gives performance metric of 100% accuracy. The experimental results of the ameliorated functionality show the effectiveness of the proposed approach.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"3 1","pages":"311-315"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73376291","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200031
Kakoli Goswami, A. B. Kandali
Aim of forecasting electrical load focuses in predicting satisfactorily and accurately the demand that might increase or decrease in the future. A large number of engineering applications count on accurate and reliable prediction models for electrical load demand. A precise forecasting of load helps in planning the capacity and operations of power companies to reliably supply energy to the consumers. In this study electrical load (L) in Assam is predicted using a data driven forecasting scheme. The study is carried out using daily 24 hourly L data obtained from SLDC, Kahilipara, Assam. The study focuses mainly on two types of regression model: ARIMA and SARIMA and also provides a performance evaluation of the models. The input data has been split into two groups of training and testing data to build the forecasting model. The correctness of the forecasting models has been assessed using the different error matrices. The final results indicated that the SARIMA model that considers the seasonality of load data provided better prediction with minimum error. MATLABR2016a was used during the entire analysis.
{"title":"Electricity Demand Prediction using Data Driven Forecasting Scheme: ARIMA and SARIMA for Real-Time Load Data of Assam","authors":"Kakoli Goswami, A. B. Kandali","doi":"10.1109/ComPE49325.2020.9200031","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200031","url":null,"abstract":"Aim of forecasting electrical load focuses in predicting satisfactorily and accurately the demand that might increase or decrease in the future. A large number of engineering applications count on accurate and reliable prediction models for electrical load demand. A precise forecasting of load helps in planning the capacity and operations of power companies to reliably supply energy to the consumers. In this study electrical load (L) in Assam is predicted using a data driven forecasting scheme. The study is carried out using daily 24 hourly L data obtained from SLDC, Kahilipara, Assam. The study focuses mainly on two types of regression model: ARIMA and SARIMA and also provides a performance evaluation of the models. The input data has been split into two groups of training and testing data to build the forecasting model. The correctness of the forecasting models has been assessed using the different error matrices. The final results indicated that the SARIMA model that considers the seasonality of load data provided better prediction with minimum error. MATLABR2016a was used during the entire analysis.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"48 2","pages":"570-574"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72599894","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200123
Alankrita, S. Srivastava, S. Gupta, A. Pandey
This paper discusses different components of hybrid renewable energy system on basis of technical parameters, sizing issues, power converter architecture and challenges faced by each of them. Since optimal operating point of whole hybrid system is required, it is necessary that not only each component operate at its own optimal operating point, but it should also complement operating point of other components. Main challenge with PV system is associated with partial shading and local maximum power point, which affects maximum power extraction from system. In case of Wind system, sizing of turbines, power fluctuation which can affect grid frequency is major issue. Battery energy storage system suffers from battery aging issues. Technical limitations of individual components can somewhat be addressed by complimentary advantage of other component and power flow fluctuation can addressed by suitable design of energy storage system. Cost of energy storage system be reduced too if extra power can be injected to the grid as in the case of grid connected system. Some hybrid system provides possibility of better resource utilization potential, while other can provide better dynamic and/or steady state performance depending on requirements. Hybrid system can also address shortcoming of one energy resource by providing complimentary parameter which can make up for such shortcoming. Factors which determine what hybrid system to choose for depends purely on requirements.
{"title":"Assessment of Technical Parameters of Renewable Energy System : An Overview","authors":"Alankrita, S. Srivastava, S. Gupta, A. Pandey","doi":"10.1109/ComPE49325.2020.9200123","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200123","url":null,"abstract":"This paper discusses different components of hybrid renewable energy system on basis of technical parameters, sizing issues, power converter architecture and challenges faced by each of them. Since optimal operating point of whole hybrid system is required, it is necessary that not only each component operate at its own optimal operating point, but it should also complement operating point of other components. Main challenge with PV system is associated with partial shading and local maximum power point, which affects maximum power extraction from system. In case of Wind system, sizing of turbines, power fluctuation which can affect grid frequency is major issue. Battery energy storage system suffers from battery aging issues. Technical limitations of individual components can somewhat be addressed by complimentary advantage of other component and power flow fluctuation can addressed by suitable design of energy storage system. Cost of energy storage system be reduced too if extra power can be injected to the grid as in the case of grid connected system. Some hybrid system provides possibility of better resource utilization potential, while other can provide better dynamic and/or steady state performance depending on requirements. Hybrid system can also address shortcoming of one energy resource by providing complimentary parameter which can make up for such shortcoming. Factors which determine what hybrid system to choose for depends purely on requirements.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"39 1","pages":"107-112"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72673784","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 this paper, we illustrate the development of a Wireless Stethoscope coupled with Bluetooth technology. The system will serve the purpose of transmitting heart sounds wirelessly to a Bluetooth receiver module, which can either be a Bluetooth speaker or a headset. This wireless technique will allow real-time transmission of heart sounds to students for better understanding. This product can serve as a teaching aid in medical institutions as multiple students can receive the transmitted sounds through earpieces, via a wireless connection.
{"title":"Wireless Stethoscope with Bluetooth Technology","authors":"Janhvi Malwade, Suaad Sayyed, Jamima Nasir, Yashada Parab, Geetha Narayanan, Shishir Gupta","doi":"10.1109/ComPE49325.2020.9200163","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200163","url":null,"abstract":"In this paper, we illustrate the development of a Wireless Stethoscope coupled with Bluetooth technology. The system will serve the purpose of transmitting heart sounds wirelessly to a Bluetooth receiver module, which can either be a Bluetooth speaker or a headset. This wireless technique will allow real-time transmission of heart sounds to students for better understanding. This product can serve as a teaching aid in medical institutions as multiple students can receive the transmitted sounds through earpieces, via a wireless connection.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"61 1","pages":"168-172"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76053878","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200100
Gourab Patowary, Meenakshi Agarwalla, S. Agarwal, M. Sarma
Land cover classification using satellite images is an important tool in the study of terrestrial resources. Satellite based information is presently available as huge sets of high resolution images from a large number of satellites like Sentinel, Landsat-8, etc. Land cover classification from these images is a difficult task because of very large sized data and high variation types. Deep Neural Networks can play a vital role in this regard and can perform classification on these large sized data. Related works in this field have used lighter models and included a large number of handcrafted parameters which requires domain knowledge on the subject. It is realised that most models are too shallow for such a complicated image. In this paper, a deeper Convolutional Neural Network (CNN) model without any satellite image specific parameters is proposed. On SAT4 and SAT6 images, our 13-layered network has achieved better accuracy upto 99.84% and 99.47% which is state-of-the-art. It is still called lightweight model because most models in Artificial Intelligence(AI)-CNN are much deeper and larger than ours.
{"title":"A Lightweight CNN Architecture for Land Classification on Satellite Images","authors":"Gourab Patowary, Meenakshi Agarwalla, S. Agarwal, M. Sarma","doi":"10.1109/ComPE49325.2020.9200100","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200100","url":null,"abstract":"Land cover classification using satellite images is an important tool in the study of terrestrial resources. Satellite based information is presently available as huge sets of high resolution images from a large number of satellites like Sentinel, Landsat-8, etc. Land cover classification from these images is a difficult task because of very large sized data and high variation types. Deep Neural Networks can play a vital role in this regard and can perform classification on these large sized data. Related works in this field have used lighter models and included a large number of handcrafted parameters which requires domain knowledge on the subject. It is realised that most models are too shallow for such a complicated image. In this paper, a deeper Convolutional Neural Network (CNN) model without any satellite image specific parameters is proposed. On SAT4 and SAT6 images, our 13-layered network has achieved better accuracy upto 99.84% and 99.47% which is state-of-the-art. It is still called lightweight model because most models in Artificial Intelligence(AI)-CNN are much deeper and larger than ours.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"82 1","pages":"362-366"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76188117","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200110
Abhishek Sharma, S. Devi, J. K. Verma
The aim of this research paper is to understand the braille system and read the book for visually impaired person without any difficulty. Braille system is used by the people who are visually impaired. Braille system consist six raised dots in each cell and each cell represent one letter in English alphabet. In this undertaking we are using KNN algorithm for find the nearest neighbors from the base dot and calculate the distance between the dots. After finding the letter raspberry pi module convert that letter into speech form by using text to speech convertor. Camera module, voice output module is attached with the Raspberry pi module. We propose a Camera based framework integrated with Image processing algorithms, KNN algorithm and text to speech module.
{"title":"Braille Book Reader using Raspberry Pi","authors":"Abhishek Sharma, S. Devi, J. K. Verma","doi":"10.1109/ComPE49325.2020.9200110","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200110","url":null,"abstract":"The aim of this research paper is to understand the braille system and read the book for visually impaired person without any difficulty. Braille system is used by the people who are visually impaired. Braille system consist six raised dots in each cell and each cell represent one letter in English alphabet. In this undertaking we are using KNN algorithm for find the nearest neighbors from the base dot and calculate the distance between the dots. After finding the letter raspberry pi module convert that letter into speech form by using text to speech convertor. Camera module, voice output module is attached with the Raspberry pi module. We propose a Camera based framework integrated with Image processing algorithms, KNN algorithm and text to speech module.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"83 1","pages":"841-843"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77419864","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200088
Rajendra Kumar, S. Khatri, Mario José Diván
The number of data centers is increasing rapidly since more people are now using cloud services for data storage and management. Due to this, the total power consumption of the data centers is also increasing. The energy efficiency of the data centers is not very high due to a variety of reasons like heat loss by equipment and power factor issues. This paper attempts to review the existing work around 2015 to 2019 and understand the issues faced by the data centers. The energy usage by the data centers and the effect of the temperatures are reviewed along with the methods of optimisation through Machine Learning (ML) algorithms. Some of the factors affecting the energy consumption of the data centers are the airflow, heat loss, ambient temperature, among others. The gap in the existing research is obtained by identifying the various factors that affect the cooling of the data centers. The effect of the cooling parameters is optimised at different locations of the data centers as per the requirement. Reinforced learning techniques have been seen to be efficient in terms of optimisation. A combination of Support Vector Machine (SVM) and Ant Colony Optimisation (ACO) is suggested as a future scope of this study.
{"title":"Effect of Cooling Systems on the Energy Efficiency of Data Centers: Machine Learning Optimisation","authors":"Rajendra Kumar, S. Khatri, Mario José Diván","doi":"10.1109/ComPE49325.2020.9200088","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200088","url":null,"abstract":"The number of data centers is increasing rapidly since more people are now using cloud services for data storage and management. Due to this, the total power consumption of the data centers is also increasing. The energy efficiency of the data centers is not very high due to a variety of reasons like heat loss by equipment and power factor issues. This paper attempts to review the existing work around 2015 to 2019 and understand the issues faced by the data centers. The energy usage by the data centers and the effect of the temperatures are reviewed along with the methods of optimisation through Machine Learning (ML) algorithms. Some of the factors affecting the energy consumption of the data centers are the airflow, heat loss, ambient temperature, among others. The gap in the existing research is obtained by identifying the various factors that affect the cooling of the data centers. The effect of the cooling parameters is optimised at different locations of the data centers as per the requirement. Reinforced learning techniques have been seen to be efficient in terms of optimisation. A combination of Support Vector Machine (SVM) and Ant Colony Optimisation (ACO) is suggested as a future scope of this study.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"43 1","pages":"596-600"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77568882","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 : 2020-07-01DOI: 10.1109/ComPE49325.2020.9200050
Santosh Kumar, C. Yadav, Barasha Mali
This paper describes the design and fabrication of a voltage tunable Microstrip line hairpin structured band-pass filter at 27.6 GHz centre frequency. To get frequency tunability, Barium Strontium Titanate (BST) based parallel plate varactor is used. Parallel plate varactor is designed in which BST is used as dielectric and the designed varactor is integrated in the microstrip line band pass filter. The schematic and layout design of the filter is designed and simulated in Advanced Design System (ADS) simulation software. For filter layout design sapphire (Ɛr =11.58) is considered as substrate and the metal electrodes used are platinum and gold. The S parameters observed are insertion loss (S21) of around -1dB and Return loss (S11) of less than −20dB. All the simulations are done in Advanced Design System (ADS).
{"title":"Design of Microstrip Tunable Bandpass Filter using Ferroelectric Thin Film Varactor","authors":"Santosh Kumar, C. Yadav, Barasha Mali","doi":"10.1109/ComPE49325.2020.9200050","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200050","url":null,"abstract":"This paper describes the design and fabrication of a voltage tunable Microstrip line hairpin structured band-pass filter at 27.6 GHz centre frequency. To get frequency tunability, Barium Strontium Titanate (BST) based parallel plate varactor is used. Parallel plate varactor is designed in which BST is used as dielectric and the designed varactor is integrated in the microstrip line band pass filter. The schematic and layout design of the filter is designed and simulated in Advanced Design System (ADS) simulation software. For filter layout design sapphire (Ɛr =11.58) is considered as substrate and the metal electrodes used are platinum and gold. The S parameters observed are insertion loss (S21) of around -1dB and Return loss (S11) of less than −20dB. All the simulations are done in Advanced Design System (ADS).","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"31 1","pages":"826-830"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81233020","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}
Food processing industries plays a vital role for the development of our country. Mango is one of the economical fruit because of its nutrient dense foods. In general, ripening stage classification done by human experts which is strenuous process and a challenging task for food processing industry. A machine learning approach for ripening stage classification has been proposed. A MATLAB based implementation shows that Ensemble classifier outperform their counter parts discriminant classifier in terms confusion matrix, average accuracy, precision, recall, specificity and F-score.So,Maturity index classification of mango plays very important role to get to know about shelf life of mangoes. Thus this paper proposes effective mango fruit grading using machine learning approaches.
{"title":"An Image Processing Approach for Grading of Mangoes based on Maturity","authors":"Md. Baig Mohammad, Lakshmi Narayana Thalluri, Renuka Devireddy, Priyanka Ch., Rajiya Sulthana","doi":"10.1109/ComPE49325.2020.9200114","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200114","url":null,"abstract":"Food processing industries plays a vital role for the development of our country. Mango is one of the economical fruit because of its nutrient dense foods. In general, ripening stage classification done by human experts which is strenuous process and a challenging task for food processing industry. A machine learning approach for ripening stage classification has been proposed. A MATLAB based implementation shows that Ensemble classifier outperform their counter parts discriminant classifier in terms confusion matrix, average accuracy, precision, recall, specificity and F-score.So,Maturity index classification of mango plays very important role to get to know about shelf life of mangoes. Thus this paper proposes effective mango fruit grading using machine learning approaches.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"58 1","pages":"512-516"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83559173","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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