Pub Date : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760975
Ying Yang, Zili Xu
This paper studies the many visual art elements that appear in the interface design of the mobile system platform from the perspective of complexity modeling, combining various interfaces. Systematic analysis and comprehensive discussion of elements such as text, color, graphics, layout and layout in visual art elements, focusing on the use and use of each art element Principles of design skills. This study clarifies that the optimal visual complexity level of the interface will vary in different tasks: the interface design that requires users to search for information should be as simple as possible; the interface that requires users to extract information should have medium complexity, and the results show that the complexity is reduced by 7.6 % Of experience
{"title":"Analysis and Application Research of Interface Design Elements for Mobile Platforms: Modeling from the Perspective of Complexity","authors":"Ying Yang, Zili Xu","doi":"10.1109/ICSCDS53736.2022.9760975","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760975","url":null,"abstract":"This paper studies the many visual art elements that appear in the interface design of the mobile system platform from the perspective of complexity modeling, combining various interfaces. Systematic analysis and comprehensive discussion of elements such as text, color, graphics, layout and layout in visual art elements, focusing on the use and use of each art element Principles of design skills. This study clarifies that the optimal visual complexity level of the interface will vary in different tasks: the interface design that requires users to search for information should be as simple as possible; the interface that requires users to extract information should have medium complexity, and the results show that the complexity is reduced by 7.6 % Of experience","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"435 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115957291","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760807
S. S, Arumugam G
Classification of multiclass datasets with the complexity of skewed data distribution is a widely discussed research area. In this paper, a novel Neighborhood based Adaptive Heterogeneous Oversampling Ensemble classifier is proposed to address the class imbalance in multidass datasets. The proposed algorithm is examined on five datasets. The performance results are compared with the benchmarking algorithms. The results revealed that the proposed method performs better than the benchmarking algorithms.
{"title":"Handling Class Imbalance in Multiclass Datasets by using a Neighborhood based Adaptive Heterogeneous Oversampling Ensemble Classifier","authors":"S. S, Arumugam G","doi":"10.1109/ICSCDS53736.2022.9760807","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760807","url":null,"abstract":"Classification of multiclass datasets with the complexity of skewed data distribution is a widely discussed research area. In this paper, a novel Neighborhood based Adaptive Heterogeneous Oversampling Ensemble classifier is proposed to address the class imbalance in multidass datasets. The proposed algorithm is examined on five datasets. The performance results are compared with the benchmarking algorithms. The results revealed that the proposed method performs better than the benchmarking algorithms.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"27 01","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120994023","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760983
Maharshi J. Dave, Rajkumar Banoth
In spite of growth in technology, Indian Judiciary system somehow lacks digitalization. In the court trials cases, every argument by the lawyers, evidence presentation, witness/suspect cross examination everything will be noted down by the stenographer and everyday hearings details will be printed at the end of every court sessions. Therefore, the details about particular case will be in physical files as well as in digital format and can be accessed whenever it is needed like in the situation of case reopening. Data integrity is important in the judiciary system; when it comes to court cases, evidence integrity must be protected because even little changes in the evidence can lead to false judgments, and historical data is crucial. Where historical data archiving is necessary, Blockchain technology is suited. In the modern era, Blockchain technology is regarded as more reliable technology than any other. Blockchain technology can be used in the justice system to provide privacy and integrity, as well as efficient auditability and traceability, for storing case records and evidences. This research study has proposed a novel method using InterPlanetary File System distributed data storage to store case details and evidences on top of the Ethereum Blockchain. The case details can be stored using text and image files. The Ethereum smart contract is used for storing hash value of data in the Blockchain. The storage and access of the data in InterPlanetary File System is studied and explained using an experimental setting.
{"title":"Blockchain-based, Decentralized Evidence Archive System using IPFS","authors":"Maharshi J. Dave, Rajkumar Banoth","doi":"10.1109/ICSCDS53736.2022.9760983","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760983","url":null,"abstract":"In spite of growth in technology, Indian Judiciary system somehow lacks digitalization. In the court trials cases, every argument by the lawyers, evidence presentation, witness/suspect cross examination everything will be noted down by the stenographer and everyday hearings details will be printed at the end of every court sessions. Therefore, the details about particular case will be in physical files as well as in digital format and can be accessed whenever it is needed like in the situation of case reopening. Data integrity is important in the judiciary system; when it comes to court cases, evidence integrity must be protected because even little changes in the evidence can lead to false judgments, and historical data is crucial. Where historical data archiving is necessary, Blockchain technology is suited. In the modern era, Blockchain technology is regarded as more reliable technology than any other. Blockchain technology can be used in the justice system to provide privacy and integrity, as well as efficient auditability and traceability, for storing case records and evidences. This research study has proposed a novel method using InterPlanetary File System distributed data storage to store case details and evidences on top of the Ethereum Blockchain. The case details can be stored using text and image files. The Ethereum smart contract is used for storing hash value of data in the Blockchain. The storage and access of the data in InterPlanetary File System is studied and explained using an experimental setting.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630870","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9761028
LiGuo Wang, Qinbo Xue
Intelligent professional competitive basketball training from the video based body tracking to smart motion prediction is studied in the paper. The research results of human motion analysis can be applied in many fields, such as intelligent monitoring system, virtual reality, human-computer interaction and motion analysis that plays a role in medicine and sports. The window- based human representation model is one of the more commonly used models in current human detection methods. The model represents the core human body as a rectangular area or a combination of several areas with a fixed relative position relationship, and does not describe the details of the human body's limbs and torso in detail. With these modelling steps, the proposed IPCBT is defined. The smart data analysis is applied fore the video information analysis. The robustness of the designed model is provided.
{"title":"Intelligent Professional Competitive Basketball Training (IPCBT): from Video based Body Tracking to Smart Motion Prediction","authors":"LiGuo Wang, Qinbo Xue","doi":"10.1109/ICSCDS53736.2022.9761028","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9761028","url":null,"abstract":"Intelligent professional competitive basketball training from the video based body tracking to smart motion prediction is studied in the paper. The research results of human motion analysis can be applied in many fields, such as intelligent monitoring system, virtual reality, human-computer interaction and motion analysis that plays a role in medicine and sports. The window- based human representation model is one of the more commonly used models in current human detection methods. The model represents the core human body as a rectangular area or a combination of several areas with a fixed relative position relationship, and does not describe the details of the human body's limbs and torso in detail. With these modelling steps, the proposed IPCBT is defined. The smart data analysis is applied fore the video information analysis. The robustness of the designed model is provided.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121571834","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760958
P. Javagar, V. Surendar, K. Jayakumar, K. A. Riyas, K. Dhanush
One of the most popular used natural resources is solar energy. Solar energy can be obtained through the use of a solar panel. The solar panel's properties indicate that it will produce the most energy when kept at a constant temperature. Solar photovoltaic energy is widely used for a variety of purposes, including heating, cooking, and power generating. The development of solar-powered vehicles has been boosted by recent inventions. The development and design of a solar charging system for electric vehicles that uses a charge controller are detailed in this project. The proposed system's implementation will decrease the electricity costs as well as charging and discharging losses. In addition, the proposed solar charging system will be one of the steps done to make the campus more environmentally friendly. Solar Power and EV charging are primary reasons for decreasing dependency on renewable resources. Electric power can be created in a variety of ways, however sustainable energy sources must be used to power electric vehicles. Electric vehicles are becoming more popular, and in the upcoming years, practically everyone will install a solar station set up in their homes
{"title":"Solar Charging Power Station for Electric Vehicle","authors":"P. Javagar, V. Surendar, K. Jayakumar, K. A. Riyas, K. Dhanush","doi":"10.1109/ICSCDS53736.2022.9760958","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760958","url":null,"abstract":"One of the most popular used natural resources is solar energy. Solar energy can be obtained through the use of a solar panel. The solar panel's properties indicate that it will produce the most energy when kept at a constant temperature. Solar photovoltaic energy is widely used for a variety of purposes, including heating, cooking, and power generating. The development of solar-powered vehicles has been boosted by recent inventions. The development and design of a solar charging system for electric vehicles that uses a charge controller are detailed in this project. The proposed system's implementation will decrease the electricity costs as well as charging and discharging losses. In addition, the proposed solar charging system will be one of the steps done to make the campus more environmentally friendly. Solar Power and EV charging are primary reasons for decreasing dependency on renewable resources. Electric power can be created in a variety of ways, however sustainable energy sources must be used to power electric vehicles. Electric vehicles are becoming more popular, and in the upcoming years, practically everyone will install a solar station set up in their homes","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125135073","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760943
Arun Pandian J, K. K., Vadem Chandu Mohan, Pulibandla Hari Krishna, Edagottu Govardhan
In this paper, a Quantum Neural Network (QNN) has been proposed using the Projected Quantum Kernel feature for an image classification task. The QCNN consists of four dense layers; the first layer collects the quantum data as an input and the fourth layer produced the classification output. Moreover, a Quantum Generative Advisory Network (QGAN) has been developed using the patching technique for enhancing the number of samples in the image dataset. The proposed QNN and QGAN are constructed using quantum filters. The MNIST handwritten digit dataset was used to train and test the QNN model performance on image classification. A binary classification dataset was created from the MNIST handwritten digit database using digits 0 and 6. The QGAN generated 221 samples on digits 0 and 6 classes. The generated samples were added to the training dataset for the QNN model. The size of the Filtered MNIST handwritten dataset was extended from 13779 to 14000 samples. There are 12,000 images are split for training and 2,000 images for testing. The principal component analysis technique was used to reduce the dimension of the data. The QNN was trained on the enhanced dataset using a GPU environment. The testing accuracy of the QNN model was 98.65 percent; it is superior to the traditional neural network.
{"title":"Quantum Generative Adversarial Network and Quantum Neural Network for Image Classification","authors":"Arun Pandian J, K. K., Vadem Chandu Mohan, Pulibandla Hari Krishna, Edagottu Govardhan","doi":"10.1109/ICSCDS53736.2022.9760943","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760943","url":null,"abstract":"In this paper, a Quantum Neural Network (QNN) has been proposed using the Projected Quantum Kernel feature for an image classification task. The QCNN consists of four dense layers; the first layer collects the quantum data as an input and the fourth layer produced the classification output. Moreover, a Quantum Generative Advisory Network (QGAN) has been developed using the patching technique for enhancing the number of samples in the image dataset. The proposed QNN and QGAN are constructed using quantum filters. The MNIST handwritten digit dataset was used to train and test the QNN model performance on image classification. A binary classification dataset was created from the MNIST handwritten digit database using digits 0 and 6. The QGAN generated 221 samples on digits 0 and 6 classes. The generated samples were added to the training dataset for the QNN model. The size of the Filtered MNIST handwritten dataset was extended from 13779 to 14000 samples. There are 12,000 images are split for training and 2,000 images for testing. The principal component analysis technique was used to reduce the dimension of the data. The QNN was trained on the enhanced dataset using a GPU environment. The testing accuracy of the QNN model was 98.65 percent; it is superior to the traditional neural network.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125596906","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760918
Haitao Liu, Yuemei Zhang
Implementation of the CodeIgniter framework for intelligent platform of social identity guiding for adolescent students in the field of recurrent parallel network is studied in the paper. The integrated information network will take the system, protocol, network, business, terminal and other aspects into consideration, realize the deep integration of space-based, space-based network and ground mobile communication network, form an integrated information network of space and earth, realize global three-dimensional coverage, meet the All-weather, all-weather ubiquitous coverage requirements for surface and three-dimensional space. With this theoretical background, the novel recurrent parallel network is designed. In order to generate efficient pipelined parallel code, it is necessary to select the appropriate computing partition layer and cyclic blocking layer from each layer of the loop, hence, the CodeIgniter framework is considered as the selection of MVC. Through the testing, robustness, efficiency are both validated.
{"title":"Implementation of CodeIgniter Framework for Intelligent Platform of Social Identity Guiding for Adolescent Students in the Field of Recurrent Parallel Network","authors":"Haitao Liu, Yuemei Zhang","doi":"10.1109/ICSCDS53736.2022.9760918","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760918","url":null,"abstract":"Implementation of the CodeIgniter framework for intelligent platform of social identity guiding for adolescent students in the field of recurrent parallel network is studied in the paper. The integrated information network will take the system, protocol, network, business, terminal and other aspects into consideration, realize the deep integration of space-based, space-based network and ground mobile communication network, form an integrated information network of space and earth, realize global three-dimensional coverage, meet the All-weather, all-weather ubiquitous coverage requirements for surface and three-dimensional space. With this theoretical background, the novel recurrent parallel network is designed. In order to generate efficient pipelined parallel code, it is necessary to select the appropriate computing partition layer and cyclic blocking layer from each layer of the loop, hence, the CodeIgniter framework is considered as the selection of MVC. Through the testing, robustness, efficiency are both validated.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122767903","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760808
N. Sasipriyaa, P. Natesan, R. Anand, P. Arvindkumar, R. S. Arwin Prakadis, K. Aswin Surya
The handwritten characters were being recognized by various people from different geographical locations for long period. In this, machine transcripts of human writings are important for transferring the statistics like political history, social life, financial life, religion, philosophy, and much more. Though this popularity of handwritten character recognition is achieved for a lot of languages such as English, Chinese, and Arabic, it is not achieved for Indian languages. The demanding situations explored through researchers in spotting a lot of curves, strokes, and holes in characters, massive character set, complicated letter structure, and less dataset. Generative Adversarial Network (GANs) is an interesting innovation in Deep Learning. Due to the least availability of the dataset for handwritten Tamil characters, GAN assists to boost the dataset. The enriched method referred to as GAN, is far feasible to get the specified quantity of dataset. The images can be conditionally generated by using a model generator of Conditional Generative Adversarial Network (cGAN). It is based upon a class label that permits the generation of a specific kind of image. A Convolutional Neural Network (CNN) is a class of artificial neural networks, used to recognize Tamil handwritten characters. The implementation of such methods has an accuracy of over 99 %. The proposed work would improve the accuracy by enhancing the dataset order of the Tamil Handwritten Character Recognition using cGAN and CNN.
{"title":"Recognizing Handwritten Offline Tamil Character by using cGAN & CNN","authors":"N. Sasipriyaa, P. Natesan, R. Anand, P. Arvindkumar, R. S. Arwin Prakadis, K. Aswin Surya","doi":"10.1109/ICSCDS53736.2022.9760808","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760808","url":null,"abstract":"The handwritten characters were being recognized by various people from different geographical locations for long period. In this, machine transcripts of human writings are important for transferring the statistics like political history, social life, financial life, religion, philosophy, and much more. Though this popularity of handwritten character recognition is achieved for a lot of languages such as English, Chinese, and Arabic, it is not achieved for Indian languages. The demanding situations explored through researchers in spotting a lot of curves, strokes, and holes in characters, massive character set, complicated letter structure, and less dataset. Generative Adversarial Network (GANs) is an interesting innovation in Deep Learning. Due to the least availability of the dataset for handwritten Tamil characters, GAN assists to boost the dataset. The enriched method referred to as GAN, is far feasible to get the specified quantity of dataset. The images can be conditionally generated by using a model generator of Conditional Generative Adversarial Network (cGAN). It is based upon a class label that permits the generation of a specific kind of image. A Convolutional Neural Network (CNN) is a class of artificial neural networks, used to recognize Tamil handwritten characters. The implementation of such methods has an accuracy of over 99 %. The proposed work would improve the accuracy by enhancing the dataset order of the Tamil Handwritten Character Recognition using cGAN and CNN.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132814483","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760987
Pramod Kumar P, A. R, Nethaji Achha, S. K, T. V, Srinivas M
In the present ingenious world, every country is accelerating in the process of developing smart cities. As a part of developing smart cities, public toilets have been entrenched at every nook and corner of the country. Yet, the hygiene and cleanliness in our country are at gunpoint due to the improper maintenance of public toilets. Because of this reason, though there are many public toilets available, people are not ready to use them with the fear of getting infected or falling sick after using the public toilet that is not properly maintained This paper proposes a new idea with the help of advancing technologies such as the Internet of Things (IoT). They are smart testing toolkits that can be installed in public toilets so that people can safely use them without any fear. It also contributes to converting the public toilets from disease transmitters to smart toilets that contribute to the health and well-being of the nation. As prevention is better than cure, the implementation of proposed idea can prevent the transmission of diseases that are caused by using the ill-maintained public toilets.
{"title":"Futuristic IoT-Enabled Toilet Maintenance System to Avoid Disease Transmission at Public Toilets in Smart Cities","authors":"Pramod Kumar P, A. R, Nethaji Achha, S. K, T. V, Srinivas M","doi":"10.1109/ICSCDS53736.2022.9760987","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760987","url":null,"abstract":"In the present ingenious world, every country is accelerating in the process of developing smart cities. As a part of developing smart cities, public toilets have been entrenched at every nook and corner of the country. Yet, the hygiene and cleanliness in our country are at gunpoint due to the improper maintenance of public toilets. Because of this reason, though there are many public toilets available, people are not ready to use them with the fear of getting infected or falling sick after using the public toilet that is not properly maintained This paper proposes a new idea with the help of advancing technologies such as the Internet of Things (IoT). They are smart testing toolkits that can be installed in public toilets so that people can safely use them without any fear. It also contributes to converting the public toilets from disease transmitters to smart toilets that contribute to the health and well-being of the nation. As prevention is better than cure, the implementation of proposed idea can prevent the transmission of diseases that are caused by using the ill-maintained public toilets.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133402123","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 : 2022-04-07DOI: 10.1109/ICSCDS53736.2022.9760850
M. Begum, R. Haris, V. Vetrimaran, P. Raj
Automated plant identification is a very promising solution for bridging the taxonomic gap, which is receiving much attention from botany and computer science. As machine learning technology advances, more complex models have been proposed to automate crop identification. Herbal remedies are considered in the pharmaceutical industry due to fewer harmful side effects and less expensive than modern medicine. Based on these data, many researchers have shown great interest in studying the recognition of natural herbal medicines. There are various possibilities for moving towards solid phase production capable of accurately discriminating medicinal plants in real time. In this project, efficient and reliable machine learning algorithms for plant catalogues using leaf images used in recent years are being studied. The review covers image processing techniques used to locate leaves and extract important leaf features from other machine learning steps. These deep learning stages are classified according to their function when it comes to discriminating leaf images based on common plant characteristics, i.e. shapes, ridges, textures and combinations of many elements. Then you get results using herbs with improved accuracy. The test results indicate that the proposed system provides an improved level of accuracy.
{"title":"Prediction of Herbs with its Benefits using Deep Learning Techniques","authors":"M. Begum, R. Haris, V. Vetrimaran, P. Raj","doi":"10.1109/ICSCDS53736.2022.9760850","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760850","url":null,"abstract":"Automated plant identification is a very promising solution for bridging the taxonomic gap, which is receiving much attention from botany and computer science. As machine learning technology advances, more complex models have been proposed to automate crop identification. Herbal remedies are considered in the pharmaceutical industry due to fewer harmful side effects and less expensive than modern medicine. Based on these data, many researchers have shown great interest in studying the recognition of natural herbal medicines. There are various possibilities for moving towards solid phase production capable of accurately discriminating medicinal plants in real time. In this project, efficient and reliable machine learning algorithms for plant catalogues using leaf images used in recent years are being studied. The review covers image processing techniques used to locate leaves and extract important leaf features from other machine learning steps. These deep learning stages are classified according to their function when it comes to discriminating leaf images based on common plant characteristics, i.e. shapes, ridges, textures and combinations of many elements. Then you get results using herbs with improved accuracy. The test results indicate that the proposed system provides an improved level of accuracy.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115074361","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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