Pub Date : 2022-11-18DOI: 10.1051/itmconf/20224403060
Sumedh Kaninde, M. Mahajan, Aditya Janghale, Bharti Joshi
Estimating stock prices has always been a challenging task for researchers in the financial sector. Although the Efficient Market Hypothesis states that it is impossible to accurately predict stock prices, there is work in the literature that has shown that stock price movements can be predicted with the right level of accuracy, if the right variables are selected and appropriate predictor models are developed. those that are flexible. The Stock Market is volatile in nature and the prediction of the same is a cumbersome task. Stock prices depend upon not only economic factors, but they relate to various physical, psychological, rational and other important parameters. In this research work, the stock prices are predicted using Facebook Prophet. Stock price predictive models have been developed and run-on published stock data acquired from Yahoo Finance. Prophet is capable of generating daily, weekly and yearly seasonality along with holiday effects, by implementing regression models. The experimental results lead to the conclusion that Facebook Prophet can be used to predict stock prices for a long period of time with reasonable accuracy.
{"title":"Stock Price Prediction using Facebook Prophet","authors":"Sumedh Kaninde, M. Mahajan, Aditya Janghale, Bharti Joshi","doi":"10.1051/itmconf/20224403060","DOIUrl":"https://doi.org/10.1051/itmconf/20224403060","url":null,"abstract":"Estimating stock prices has always been a challenging task for researchers in the financial sector. Although the Efficient Market Hypothesis states that it is impossible to accurately predict stock prices, there is work in the literature that has shown that stock price movements can be predicted with the right level of accuracy, if the right variables are selected and appropriate predictor models are developed. those that are flexible. The Stock Market is volatile in nature and the prediction of the same is a cumbersome task. Stock prices depend upon not only economic factors, but they relate to various physical, psychological, rational and other important parameters. In this research work, the stock prices are predicted using Facebook Prophet. Stock price predictive models have been developed and run-on published stock data acquired from Yahoo Finance. Prophet is capable of generating daily, weekly and yearly seasonality along with holiday effects, by implementing regression models. The experimental results lead to the conclusion that Facebook Prophet can be used to predict stock prices for a long period of time with reasonable accuracy.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126500343","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 : 2022-01-01DOI: 10.1051/itmconf/20224703035
Weihua Luo, Xiaolong Yang, Sheng Qiao
Lithium-ion batteries (LIBs) are widely used in electric vehicles, while capacity fading happens due to unwanted side reactions during cycling. Therefore, it is of great significance to study the aging mechanisms of LIBs among the whole life cycle for the use and design of LIBs. In this study, the aging experiments of Graphite/LiNi0.80Co0.15Al0.05O2 (NCA) batteries were conducted at 25°C and 45°C, the aging mechanisms were examined by differential voltage analysis method and electrochemical impedance spectroscopy analysis method, and verified by microscopic morphology observation. The results show that the loss of anode active material and lithium ions are the main degradation modes, and the lithium plating side reaction at the late aging stage is the inducement of capacity plunge both at 25°C and 45°C. But the causes of lithium plating are different, at 25 °C, the growth of solid electrolyte interphase (SEI) leads to lithium plating, while at 45 °C, the accumulation of gas leads to lithium plating.
{"title":"Aging mechanisms analysis of Graphite/LiNi0.80Co0.15Al0.05O2 lithium-ion batteries among the whole life cycle at different temperatures","authors":"Weihua Luo, Xiaolong Yang, Sheng Qiao","doi":"10.1051/itmconf/20224703035","DOIUrl":"https://doi.org/10.1051/itmconf/20224703035","url":null,"abstract":"Lithium-ion batteries (LIBs) are widely used in electric vehicles, while capacity fading happens due to unwanted side reactions during cycling. Therefore, it is of great significance to study the aging mechanisms of LIBs among the whole life cycle for the use and design of LIBs. In this study, the aging experiments of Graphite/LiNi0.80Co0.15Al0.05O2 (NCA) batteries were conducted at 25°C and 45°C, the aging mechanisms were examined by differential voltage analysis method and electrochemical impedance spectroscopy analysis method, and verified by microscopic morphology observation. The results show that the loss of anode active material and lithium ions are the main degradation modes, and the lithium plating side reaction at the late aging stage is the inducement of capacity plunge both at 25°C and 45°C. But the causes of lithium plating are different, at 25 °C, the growth of solid electrolyte interphase (SEI) leads to lithium plating, while at 45 °C, the accumulation of gas leads to lithium plating.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131320784","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 : 2022-01-01DOI: 10.1051/itmconf/20224403030
Adinath Joshi, Atharva Kamble, Akanksha Parate, Siddhesh Parkar, D. Puri, Chandrakant J. Gaikwad
Drowsiness is described as a state of reduced consciousness and vigilance accompanied by a desire or want to sleep. Driver tiredness is frequently detected using wearable sensors that track vehicle movement and camera-based systems that track driver behavior. Many alternative EEG-based drowsiness detection systems are developed due to the potential of electroencephalogram (EEG) signals to observe human mood and the ease with which they may be obtained. This paper applies Deep learning architecture like Convolutional Neural networks (CNN) and algorithms for the classification of EEG data for Drowsiness Detection. The key measures of video-based approaches include the detection of physical features; nevertheless, problems such as brightness limitations and practical challenges such as driver attention limits its usefulness. The main measure of video-based methods is the degree of closure of the eyelids; however, its success is limited by constraints like as brightness restrictions and practical challenges such as driver distraction. We have extracted statistical features and trained using various classifiers like Logistic Regression, Naïve Bayes, SVM, and K Nearest Neighbours and compared the accuracy using a deep learning CNN model. Results demonstrate that CNN achieved an accuracy of 94.75% by delegating feature extraction on itself. Upon comparing existing state–of–the–art drowsiness detection systems, the testing results reveal a higher detection capability. The results show that the the suggested method can be used to develop a reliable EEG-based driving drowsiness detection system.
{"title":"Drowsiness Detection using EEG signals and Machine Learning Algorithms","authors":"Adinath Joshi, Atharva Kamble, Akanksha Parate, Siddhesh Parkar, D. Puri, Chandrakant J. Gaikwad","doi":"10.1051/itmconf/20224403030","DOIUrl":"https://doi.org/10.1051/itmconf/20224403030","url":null,"abstract":"Drowsiness is described as a state of reduced consciousness and vigilance accompanied by a desire or want to sleep. Driver tiredness is frequently detected using wearable sensors that track vehicle movement and camera-based systems that track driver behavior. Many alternative EEG-based drowsiness detection systems are developed due to the potential of electroencephalogram (EEG) signals to observe human mood and the ease with which they may be obtained. This paper applies Deep learning architecture like Convolutional Neural networks (CNN) and algorithms for the classification of EEG data for Drowsiness Detection. The key measures of video-based approaches include the detection of physical features; nevertheless, problems such as brightness limitations and practical challenges such as driver attention limits its usefulness. The main measure of video-based methods is the degree of closure of the eyelids; however, its success is limited by constraints like as brightness restrictions and practical challenges such as driver distraction. We have extracted statistical features and trained using various classifiers like Logistic Regression, Naïve Bayes, SVM, and K Nearest Neighbours and compared the accuracy using a deep learning CNN model. Results demonstrate that CNN achieved an accuracy of 94.75% by delegating feature extraction on itself. Upon comparing existing state–of–the–art drowsiness detection systems, the testing results reveal a higher detection capability. The results show that the the suggested method can be used to develop a reliable EEG-based driving drowsiness detection system.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124809446","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}
Detecting objects in real-time and converting them into an audio output was a challenging task. Recent advancement in computer vision has allowed the development of various real-time object detection applications. This paper describes a simple android app that would help the visually impaired people in understanding their surroundings. The information about the surrounding environment was captured through a phone’s camera where real-time object recognition through tensorflow’s object detection API was done. The detected objects were then converted into an audio output by using android’s text-to-speech library. Tensorflow lite made the offline processing of complex algorithms simple. The overall accuracy of the proposed system was found to be approximately 90%.
{"title":"Android-based object recognition application for visually impaired","authors":"Akilesh Salunkhe, Manthan Raut, Shayantan Santra, Sumedha Bhagwat","doi":"10.1051/itmconf/20214003001","DOIUrl":"https://doi.org/10.1051/itmconf/20214003001","url":null,"abstract":"Detecting objects in real-time and converting them into an audio output was a challenging task. Recent advancement in computer vision has allowed the development of various real-time object detection applications. This paper describes a simple android app that would help the visually impaired people in understanding their surroundings. The information about the surrounding environment was captured through a phone’s camera where real-time object recognition through tensorflow’s object detection API was done. The detected objects were then converted into an audio output by using android’s text-to-speech library. Tensorflow lite made the offline processing of complex algorithms simple. The overall accuracy of the proposed system was found to be approximately 90%.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843899","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}
Le travail que nous présentons dans cet article vise la redynamisation de l’enseignement-apprentissage du produit scalaire via la conception d’une séquence d’introduction de cette notion au lycée et des modalités de sa mise en oeuvre par l’enseignant. Cet intérêt est justifié par le manque d’activités motivantes dans les manuels marocains que nous avons consultés et par le fait que la construction de cette notion mobilise des objets mathématiques susceptibles de cumuler des difficultés d’apprentissages telles que les notions de vecteur et de produit. La démarche adoptée dans cette recherche, se base sur le constructivisme comme théorie d’apprentissage, l’approche interdisciplinaire pour donner plus de sens aux savoirs construits et l’intégration de la géométrie dynamique permettant de conjecture du résultat dans sa généralité en couvrant tous les cas de figures possibles et la construction éventuelle des figures dynamiques par les apprenants. Ainsi ; nous avons choisi comme activité d’approche une situation authentique dont la résolution fait appel essentiellement à la notion de résultante de deux forces que les apprenants ont déjà abordée en mécanique, et aux notions de somme de deux vecteurs et le théorème de Pythagore vus en mathématiques.
{"title":"Conception d’une séquence d’introduction dynamique du produit scalaire via une approche constructiviste intégrant la mécanique et les TIC","authors":"Khadija Raouf, Najia Benkenza, M’hamed El Aydi, Mohamed Anaya, Khalid Ennaciri","doi":"10.1051/ITMCONF/20213901007","DOIUrl":"https://doi.org/10.1051/ITMCONF/20213901007","url":null,"abstract":"Le travail que nous présentons dans cet article vise la redynamisation de l’enseignement-apprentissage du produit scalaire via la conception d’une séquence d’introduction de cette notion au lycée et des modalités de sa mise en oeuvre par l’enseignant. Cet intérêt est justifié par le manque d’activités motivantes dans les manuels marocains que nous avons consultés et par le fait que la construction de cette notion mobilise des objets mathématiques susceptibles de cumuler des difficultés d’apprentissages telles que les notions de vecteur et de produit. La démarche adoptée dans cette recherche, se base sur le constructivisme comme théorie d’apprentissage, l’approche interdisciplinaire pour donner plus de sens aux savoirs construits et l’intégration de la géométrie dynamique permettant de conjecture du résultat dans sa généralité en couvrant tous les cas de figures possibles et la construction éventuelle des figures dynamiques par les apprenants. Ainsi ; nous avons choisi comme activité d’approche une situation authentique dont la résolution fait appel essentiellement à la notion de résultante de deux forces que les apprenants ont déjà abordée en mécanique, et aux notions de somme de deux vecteurs et le théorème de Pythagore vus en mathématiques.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117338224","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 : 2021-01-26DOI: 10.1051/ITMCONF/20213601005
Moinak Bhaduri, D. Rangan, Anurag Balaji
Detecting changes in an incoming data flow is immensely crucial for understanding inherent dependencies, formulating new or adapting existing policies, and anticipating further changes. Distinct modeling constructs have triggered varied ways of detecting such changes, almost every one of which gives in to certain shortcomings. Parametric models based on time series objects, for instance, work well under distributional assumptions or when change detection in specific properties - such as mean, variance, trend, etc. are of interest. Others rely heavily on the “at most one change-point” assumption, and implementing binary segmentation to discover subsequent changes comes at a hefty computational cost. This work offers an alternative that remains both versatile and untethered to such stifling constraints. Detection is done through a sequence of tests with variations to certain trend permuted statistics. We study non-stationary Hawkes patterns which, with an underlying stochastic intensity, imply a natural branching process structure. Our proposals are shown to estimate changes efficiently in both the immigrant and the offspring intensity without sounding too many false positives. Comparisons with established competitors reveal smaller Hausdorff-based estimation errors, desirable inferential properties such as asymptotic consistency and narrower bootstrapped margins. Four real data sets on NASDAQ price movements, crude oil prices, tsunami occurrences, and COVID-19 infections have been analyzed. Forecasting methods are also touched upon.
{"title":"Change detection in non-stationary Hawkes processes through sequential testing","authors":"Moinak Bhaduri, D. Rangan, Anurag Balaji","doi":"10.1051/ITMCONF/20213601005","DOIUrl":"https://doi.org/10.1051/ITMCONF/20213601005","url":null,"abstract":"Detecting changes in an incoming data flow is immensely crucial for understanding inherent dependencies, formulating new or adapting existing policies, and anticipating further changes. Distinct modeling constructs have triggered varied ways of detecting such changes, almost every one of which gives in to certain shortcomings. Parametric models based on time series objects, for instance, work well under distributional assumptions or when change detection in specific properties - such as mean, variance, trend, etc. are of interest. Others rely heavily on the “at most one change-point” assumption, and implementing binary segmentation to discover subsequent changes comes at a hefty computational cost. This work offers an alternative that remains both versatile and untethered to such stifling constraints. Detection is done through a sequence of tests with variations to certain trend permuted statistics. We study non-stationary Hawkes patterns which, with an underlying stochastic intensity, imply a natural branching process structure. Our proposals are shown to estimate changes efficiently in both the immigrant and the offspring intensity without sounding too many false positives. Comparisons with established competitors reveal smaller Hausdorff-based estimation errors, desirable inferential properties such as asymptotic consistency and narrower bootstrapped margins. Four real data sets on NASDAQ price movements, crude oil prices, tsunami occurrences, and COVID-19 infections have been analyzed. Forecasting methods are also touched upon.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115124519","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 : 1900-01-01DOI: 10.1051/itmconf/20224201005
Kamaran H. Manguri, Saman M. Omer
Recently, it has emerged that both Internet of Things (IoT), and Software Defined Network (SDN) are becoming popular technologies. The main goal of IoT is to link electronic devices via the internet, meanwhile SDN facilitates network arrangement for management of a network by distinguishing the control layer and the data layer from each other. The number of electronic devices over the internet is increasing constantly, therefore it is a complicated process to manage and control especially over the huge distributed network. IoT network can be reasonably flexible and programmable through The SDN without introducing any trouble to the previously implemented network infrastructure. This paper reviews various IoT domains and applications such as cellular network, wireless Sensor, IoT management, security and smart city framework and common IoT SDN solutions. Moreover, The IoT and SDN notion has been explored critically, with assessing the current contributions in the research field. Lastly, analyzing current available solutions for SDN-based IoT implementations comparatively helps easily understanding the emerging trends view.
{"title":"SDN for IoT Environment: A Survey and Research Challenges","authors":"Kamaran H. Manguri, Saman M. Omer","doi":"10.1051/itmconf/20224201005","DOIUrl":"https://doi.org/10.1051/itmconf/20224201005","url":null,"abstract":"Recently, it has emerged that both Internet of Things (IoT), and Software Defined Network (SDN) are becoming popular technologies. The main goal of IoT is to link electronic devices via the internet, meanwhile SDN facilitates network arrangement for management of a network by distinguishing the control layer and the data layer from each other. The number of electronic devices over the internet is increasing constantly, therefore it is a complicated process to manage and control especially over the huge distributed network. IoT network can be reasonably flexible and programmable through The SDN without introducing any trouble to the previously implemented network infrastructure. This paper reviews various IoT domains and applications such as cellular network, wireless Sensor, IoT management, security and smart city framework and common IoT SDN solutions. Moreover, The IoT and SDN notion has been explored critically, with assessing the current contributions in the research field. Lastly, analyzing current available solutions for SDN-based IoT implementations comparatively helps easily understanding the emerging trends view.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114998295","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 : 1900-01-01DOI: 10.1051/itmconf/20193007008
O. Matveev, M. Morozova
The features of the propagation of spin waves in a composite multiferroic structure consisting of two magnonic crystals and a ferroelectric layer are considered. During the propagation of spin waves in such a structure, the formation of band gaps takes place, the position of which depends on the method of excitation of coupled structure and dielectric constant of ferroelectric. This effect can be taken as the basis for the operation of a logical element that allows implementing AND and OR operators. The results of theoretical and experimental studies of spin-wave processes in this structure are presented.
{"title":"Concept of using structure magnonic crystal – ferroelectric – magnonic crystal as logic gate","authors":"O. Matveev, M. Morozova","doi":"10.1051/itmconf/20193007008","DOIUrl":"https://doi.org/10.1051/itmconf/20193007008","url":null,"abstract":"The features of the propagation of spin waves in a composite multiferroic structure consisting of two magnonic crystals and a ferroelectric layer are considered. During the propagation of spin waves in such a structure, the formation of band gaps takes place, the position of which depends on the method of excitation of coupled structure and dielectric constant of ferroelectric. This effect can be taken as the basis for the operation of a logical element that allows implementing AND and OR operators. The results of theoretical and experimental studies of spin-wave processes in this structure are presented.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123125142","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 : 1900-01-01DOI: 10.1051/itmconf/20224701018
Yifan Zhang, Liu Chong
Based on the detected vibration signal, a measurement system was designed to solve the current problem of closed centrifuge speed measurement. The system collected and adjusted the signal collected by the vibration sensor, and then send it to the control unit STM32 for spectrum analysis to get the speed frequency. The sampling data was analysed and processed in PC through serial communication. Programs were written to achieve data sampling, filtering and storage, and the important parameters such as acceleration waveforms, vibration frequency and actual speed were displayed on the screen. The experimental results show that the system can accurately calculate the real-time speed of the closed centrifuge according to the measured vibration signals, which has the advantages of high stability, detection accuracy and real-time performance.
{"title":"A speed measuring system of hermetic centrifuge","authors":"Yifan Zhang, Liu Chong","doi":"10.1051/itmconf/20224701018","DOIUrl":"https://doi.org/10.1051/itmconf/20224701018","url":null,"abstract":"Based on the detected vibration signal, a measurement system was designed to solve the current problem of closed centrifuge speed measurement. The system collected and adjusted the signal collected by the vibration sensor, and then send it to the control unit STM32 for spectrum analysis to get the speed frequency. The sampling data was analysed and processed in PC through serial communication. Programs were written to achieve data sampling, filtering and storage, and the important parameters such as acceleration waveforms, vibration frequency and actual speed were displayed on the screen. The experimental results show that the system can accurately calculate the real-time speed of the closed centrifuge according to the measured vibration signals, which has the advantages of high stability, detection accuracy and real-time performance.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124366666","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 : 1900-01-01DOI: 10.1051/itmconf/20214003043
Ishaan Agrawal, Prada Hegde, P. Shetty, Priyanka Shingane
Identification of plant disease is tough in agribusiness arena. If it is inaccurate, there occurs a tremendous damage in the production and economical price. Leaf Disease detection requires huge amount of work, knowledge, processing time in plant disease. The most used and edible vegetable all over the world is from cucurbitaceous family. The crops under this family have great economic value in the food industry and its production is done in large scale. This family consists of 965 species. If any of these plants catch disease then there would be a tremendous loss in the production of this field yields. Thus, treating them at early stage is best way to prevent such losses. Hence, Deep Learning Algorithm like CNN can be used to detect the diseases of the plants. The leaves of the plants would be used as primary material for identification of the disease, as they are much more visible on the leaves.
{"title":"LEAF DISEASE DETECTION OF CUCURBITS USING CNN","authors":"Ishaan Agrawal, Prada Hegde, P. Shetty, Priyanka Shingane","doi":"10.1051/itmconf/20214003043","DOIUrl":"https://doi.org/10.1051/itmconf/20214003043","url":null,"abstract":"Identification of plant disease is tough in agribusiness arena. If it is inaccurate, there occurs a tremendous damage in the production and economical price. Leaf Disease detection requires huge amount of work, knowledge, processing time in plant disease. The most used and edible vegetable all over the world is from cucurbitaceous family. The crops under this family have great economic value in the food industry and its production is done in large scale. This family consists of 965 species. If any of these plants catch disease then there would be a tremendous loss in the production of this field yields. Thus, treating them at early stage is best way to prevent such losses. Hence, Deep Learning Algorithm like CNN can be used to detect the diseases of the plants. The leaves of the plants would be used as primary material for identification of the disease, as they are much more visible on the leaves.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124386986","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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