Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544621
Yadeeswaran K S, N.Mithun Mithra, Varsha Ks, K. R
Diabetic retinopathy is a condition caused due to diabetes affecting the blood vessels in the retina. This paper presents a two-phase approach for diagnosing various conditions of the eye and also classify the fundus image as diabetic retinopathy positive or normal. The ODIR dataset containing fundus images of various conditions is used for training and testing purposes. The proposed method consists of an ensemble model. The first phase is a convolutional neural network that takes fundus images for its input and outputs the diagnostic keywords for each eye. The second phase is a machine learning classifier that determines if a person has diabetic retinopathy or not based on the keywords generated from the previous model. The results of the two phases are satisfactory. The diagnosing phase has an accuracy up to 95% and the classifier has an accuracy up to 99%.
{"title":"Classification of diabetic retinopathy through identification of diagnostic keywords","authors":"Yadeeswaran K S, N.Mithun Mithra, Varsha Ks, K. R","doi":"10.1109/ICIRCA51532.2021.9544621","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544621","url":null,"abstract":"Diabetic retinopathy is a condition caused due to diabetes affecting the blood vessels in the retina. This paper presents a two-phase approach for diagnosing various conditions of the eye and also classify the fundus image as diabetic retinopathy positive or normal. The ODIR dataset containing fundus images of various conditions is used for training and testing purposes. The proposed method consists of an ensemble model. The first phase is a convolutional neural network that takes fundus images for its input and outputs the diagnostic keywords for each eye. The second phase is a machine learning classifier that determines if a person has diabetic retinopathy or not based on the keywords generated from the previous model. The results of the two phases are satisfactory. The diagnosing phase has an accuracy up to 95% and the classifier has an accuracy up to 99%.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129124606","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}
Over the years with the advent of social media and messaging apps, people have been using jargon, abbreviated words, and casual language while chatting with other people. This leads to a lack of conversational skills during interviews, job meetings, or even daily conversations. Poorly spoken English has been a prime factor due to which students are unsuccessful in clearing the interviews for a job. There are many studies that indicate that an overwhelming percentage of engineers in the country cannot speak English fluently which is required for high-end consulting jobs. Present-day institutions provide solutions for improving English speaking but are expensive. Hence, there is a need for an instantly available conversing partner to hone communication skills. We propose a virtual assistant that can communicate with the user in an attempt to improve English speaking skills. The system consists of SynQG model for question generation, RoBERTa Grammar Error Correction model and praat-parselmouth for speech analysis. The user practices English speaking by answering the questions generated by the system. A thorough speech analysis report is provided to the user based on these answers highlighting mistakes as well as strengths in areas like grammar and pronunciation.
{"title":"Virtual Assistant for Enhancing English Speaking Skills","authors":"Ayushi Desai, Yash Gandhi, Jaynil Gaglani, Nikahat Mulla","doi":"10.1109/ICIRCA51532.2021.9544877","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544877","url":null,"abstract":"Over the years with the advent of social media and messaging apps, people have been using jargon, abbreviated words, and casual language while chatting with other people. This leads to a lack of conversational skills during interviews, job meetings, or even daily conversations. Poorly spoken English has been a prime factor due to which students are unsuccessful in clearing the interviews for a job. There are many studies that indicate that an overwhelming percentage of engineers in the country cannot speak English fluently which is required for high-end consulting jobs. Present-day institutions provide solutions for improving English speaking but are expensive. Hence, there is a need for an instantly available conversing partner to hone communication skills. We propose a virtual assistant that can communicate with the user in an attempt to improve English speaking skills. The system consists of SynQG model for question generation, RoBERTa Grammar Error Correction model and praat-parselmouth for speech analysis. The user practices English speaking by answering the questions generated by the system. A thorough speech analysis report is provided to the user based on these answers highlighting mistakes as well as strengths in areas like grammar and pronunciation.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130257144","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544669
Malathy. S, C. Vanitha, Nirdhum Narayan, Rajesh Kumar, Gokul. R
Handwritten digit recognition have great impact in the applications of deep learning. Convolutional Neural Network in the deep learning has become one of the major methods and one of the important factors in the various success in recent times and deep learning is used majorly in the area of object recognition. In the paper work, the speech output feature is integrated along with the text output. Convolutional Neural Network model is applied in the image classification. The dataset used to train and test is the MNIST dataset. There are various applications of handwritten digit recognition in the real time. It is applied in detection of vehicle number, reading of bank cheques, the arrangement of letters in the post office.
{"title":"An Enhanced Handwritten Digit Recognition Using Convolutional Neural Network","authors":"Malathy. S, C. Vanitha, Nirdhum Narayan, Rajesh Kumar, Gokul. R","doi":"10.1109/ICIRCA51532.2021.9544669","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544669","url":null,"abstract":"Handwritten digit recognition have great impact in the applications of deep learning. Convolutional Neural Network in the deep learning has become one of the major methods and one of the important factors in the various success in recent times and deep learning is used majorly in the area of object recognition. In the paper work, the speech output feature is integrated along with the text output. Convolutional Neural Network model is applied in the image classification. The dataset used to train and test is the MNIST dataset. There are various applications of handwritten digit recognition in the real time. It is applied in detection of vehicle number, reading of bank cheques, the arrangement of letters in the post office.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129500391","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545042
V. G, S. Thangam
Internet of things (IOT) is a technology trend in modern innovation which provides answers for issues in our standard of living. IOT is being applied in modernization of many spaces of life. IOT can also be utilized to solve issues in traditional agriculture methods and agribusiness area to naturally keep up and screen rural homesteads with insignificant human association. The paper highlights numerous parts of innovations associated with the space of IOT in farming and role of IOT in agribusiness. The impact of inclusion of IOT in organization advancements in IOT based agribusiness has been introduced, that includes sensors, actuators, network engineering, wireless technologies and architectural layers, network geographies utilized, and conventions.
{"title":"Smart agriculture and role of IOT","authors":"V. G, S. Thangam","doi":"10.1109/ICIRCA51532.2021.9545042","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545042","url":null,"abstract":"Internet of things (IOT) is a technology trend in modern innovation which provides answers for issues in our standard of living. IOT is being applied in modernization of many spaces of life. IOT can also be utilized to solve issues in traditional agriculture methods and agribusiness area to naturally keep up and screen rural homesteads with insignificant human association. The paper highlights numerous parts of innovations associated with the space of IOT in farming and role of IOT in agribusiness. The impact of inclusion of IOT in organization advancements in IOT based agribusiness has been introduced, that includes sensors, actuators, network engineering, wireless technologies and architectural layers, network geographies utilized, and conventions.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128253681","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544635
Nasrin Aasofwala, Shanti Verma, Kalyani Patel
Deaf Culture is important for deaf community as it is everywhere in the world. Deaf people are using Visual language (Sign language) for communicating. There are around 300 different types of sign languages are available in the globe like British Sign Language, Indonesian Sign Language, American sign language, etc. Each sign language has its own syntax and semantics. Some sign languages are using one hand gesture, some are using two hand gesture as they have their own rules for communication. There is a need of one standard form of sign language so it will be easier to understand. There are so many challenges and problems are facing by deaf community. Different sign languages are provided different solutions for speech to sign language and sign language to speech conversion. As there is no solution is provided by anyone for Gujarati Sign Language, we proposed a one communication model for Speech to Sign language. Speech will be recognized and convert into text, text will give the HamNoSys Notation (Sign language Notation) from a database and then it converts in SiGML format and then it display a sign animation (Avatar). That model will be helpful to Gujarat region deaf and dumb people for communicating with normal people.
{"title":"A Novel Speech to Sign Communication Model for Gujarati Language","authors":"Nasrin Aasofwala, Shanti Verma, Kalyani Patel","doi":"10.1109/ICIRCA51532.2021.9544635","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544635","url":null,"abstract":"Deaf Culture is important for deaf community as it is everywhere in the world. Deaf people are using Visual language (Sign language) for communicating. There are around 300 different types of sign languages are available in the globe like British Sign Language, Indonesian Sign Language, American sign language, etc. Each sign language has its own syntax and semantics. Some sign languages are using one hand gesture, some are using two hand gesture as they have their own rules for communication. There is a need of one standard form of sign language so it will be easier to understand. There are so many challenges and problems are facing by deaf community. Different sign languages are provided different solutions for speech to sign language and sign language to speech conversion. As there is no solution is provided by anyone for Gujarati Sign Language, we proposed a one communication model for Speech to Sign language. Speech will be recognized and convert into text, text will give the HamNoSys Notation (Sign language Notation) from a database and then it converts in SiGML format and then it display a sign animation (Avatar). That model will be helpful to Gujarat region deaf and dumb people for communicating with normal people.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129027239","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544800
E. Zhang
Uterine fibroids are the most common benign tumors in gynecology, with high incidence rate and showing an increasing trend. Some uterine fibroids can lead to patients with prolonged menstrual cycle, increased menstrual volume, more severe cases will appear hemorrhagic anemia. Larger uterine fibroids will oppress the patient's pelvic cavity, so that patients have frequent urination, fecal discomfort, etc. This disease seriously affects women's life and health. This paper completes the requirement analysis and overall design of the disease data mining system. After that, the system is divided into data processing subsystem, algorithm calling subsystem, knowledge display subsystem, user management subsystem, as well as the realization technology, function modules and main process of the main functions of the system.
{"title":"Clinical Study on Fast Rehabilitation Program of Integrated Traditional Chinese and Western Medicine after Laparoscopic Hysterectomy based on Data Mining","authors":"E. Zhang","doi":"10.1109/ICIRCA51532.2021.9544800","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544800","url":null,"abstract":"Uterine fibroids are the most common benign tumors in gynecology, with high incidence rate and showing an increasing trend. Some uterine fibroids can lead to patients with prolonged menstrual cycle, increased menstrual volume, more severe cases will appear hemorrhagic anemia. Larger uterine fibroids will oppress the patient's pelvic cavity, so that patients have frequent urination, fecal discomfort, etc. This disease seriously affects women's life and health. This paper completes the requirement analysis and overall design of the disease data mining system. After that, the system is divided into data processing subsystem, algorithm calling subsystem, knowledge display subsystem, user management subsystem, as well as the realization technology, function modules and main process of the main functions of the system.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123184628","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544796
A. Sasi, Sathish Kumar Ravichandran
Spatial Computation is the next step in the continuing convergence between the digital and physical realms. It is a set of inventions and developments that can better our lives through learning the real world, acknowledging and connecting our connection to, and traveling through various locations in the world. The lack of modern, precise, and effective diagnosis limits the rehabilitation of patients, despite technical advancements in medicines. The capabilities of spatial computing are expanded in a healthcare framework during the care and treatment of the patient. In this article, our purpose is to clarify the function of ProjectDR in the field of healthcare, which enables the display of medical images, such as CT scans and MRI results, directly on the patient's body in a manner that moves as patients do.
{"title":"Future Innovation in Healthcare by Spatial Computing using ProjectDR","authors":"A. Sasi, Sathish Kumar Ravichandran","doi":"10.1109/ICIRCA51532.2021.9544796","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544796","url":null,"abstract":"Spatial Computation is the next step in the continuing convergence between the digital and physical realms. It is a set of inventions and developments that can better our lives through learning the real world, acknowledging and connecting our connection to, and traveling through various locations in the world. The lack of modern, precise, and effective diagnosis limits the rehabilitation of patients, despite technical advancements in medicines. The capabilities of spatial computing are expanded in a healthcare framework during the care and treatment of the patient. In this article, our purpose is to clarify the function of ProjectDR in the field of healthcare, which enables the display of medical images, such as CT scans and MRI results, directly on the patient's body in a manner that moves as patients do.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125916686","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544606
L. Ding, Wei-Hau Du
This research study begins with deep learning and progresses to cluster computing to complete the image depth analysis pipeline. The deep neural model is taken into account in designing the proposed model. The convolutional layer is composed of several convolutional units in morphology, and the feature value of the related image is obtained through the convolution and operation. The parallel structure is utilized to optimize this layer. Further, the original data is taken as input, and complete the construction of the proposed model through a series of operations such as convolution, pooling, and nonlinear activation function mapping. The depth image analysis is selected as the verification target. Through the simulation, the analysis accuracy has been much higher than the traditional methods.
{"title":"Image Depth Analysis: From Deep Learning to Parallel Cluster Computing","authors":"L. Ding, Wei-Hau Du","doi":"10.1109/ICIRCA51532.2021.9544606","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544606","url":null,"abstract":"This research study begins with deep learning and progresses to cluster computing to complete the image depth analysis pipeline. The deep neural model is taken into account in designing the proposed model. The convolutional layer is composed of several convolutional units in morphology, and the feature value of the related image is obtained through the convolution and operation. The parallel structure is utilized to optimize this layer. Further, the original data is taken as input, and complete the construction of the proposed model through a series of operations such as convolution, pooling, and nonlinear activation function mapping. The depth image analysis is selected as the verification target. Through the simulation, the analysis accuracy has been much higher than the traditional methods.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127613431","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544100
Ashutosh Upadhyay, K. S.
Computer vision mainly focuses on the automatic extraction, analysis, and understanding of useful information from a single image or video. On the other hand, authenticity is emerging as one of the primary requirements in today's world by developing a system for computer vision complexity. Generally, two robust techniques such as age estimation and face recognition are required to maintain authenticity. In reality, fraud and scams are getting increased, so here this paper has proposed a new combined model for face recognition and age prediction. Face recognition has been implemented and presented in this paper by using a Deep Neural Network. The authenticity problem can be handled by using either facial recognition or age prediction alone; this study has presented a method that employs both of them together to enhance the system's robustness. So, first, this model detects the person's face, and then it predicts the person's age. If the individual is eligible to view the information or perform a task, their access will be limited; otherwise, their access will be restricted. So it helps to solve two difficulties in this case: the person's identification cannot be faked, and their age is also confirmed by the system. (CNN for the face, and mention technique for the age.)
{"title":"AI-based content filtering system using an age prediction algorithm","authors":"Ashutosh Upadhyay, K. S.","doi":"10.1109/ICIRCA51532.2021.9544100","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544100","url":null,"abstract":"Computer vision mainly focuses on the automatic extraction, analysis, and understanding of useful information from a single image or video. On the other hand, authenticity is emerging as one of the primary requirements in today's world by developing a system for computer vision complexity. Generally, two robust techniques such as age estimation and face recognition are required to maintain authenticity. In reality, fraud and scams are getting increased, so here this paper has proposed a new combined model for face recognition and age prediction. Face recognition has been implemented and presented in this paper by using a Deep Neural Network. The authenticity problem can be handled by using either facial recognition or age prediction alone; this study has presented a method that employs both of them together to enhance the system's robustness. So, first, this model detects the person's face, and then it predicts the person's age. If the individual is eligible to view the information or perform a task, their access will be limited; otherwise, their access will be restricted. So it helps to solve two difficulties in this case: the person's identification cannot be faked, and their age is also confirmed by the system. (CNN for the face, and mention technique for the age.)","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"22 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114105171","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545009
Yashvi Desai, Naisha Shah, Vrushali Shah, P. Bhavathankar, Kaisar Katchi
Augmented reality has three principal features: combining the real world environment with the virtual world, real-time interaction for users, and accurate representation of 3D objects. Augmented Reality in E-commerce allows customers to view products or experience services in their physical space before purchasing the required items. Current online shopping services only allow customers to see 2D images of the products they are buying. This type of experience is not personalized and sometimes leads to bad shopping choices choices; the customers find it difficult to shop only with a static image view available. Customers cannot accurately predict whether the product they purchase will fit their home environment. This results in a lot of people returning or exchanging the things their purchases. AR resolves these issues. Thus, a method has been proposed for adding a virtual object in the real world by just using a real-time camera. The main aim of this paper is to provide user visualization of high resolution E-commerce products in a real environment.
{"title":"Markerless Augmented Reality based application for E-Commerce to Visualise 3D Content","authors":"Yashvi Desai, Naisha Shah, Vrushali Shah, P. Bhavathankar, Kaisar Katchi","doi":"10.1109/ICIRCA51532.2021.9545009","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545009","url":null,"abstract":"Augmented reality has three principal features: combining the real world environment with the virtual world, real-time interaction for users, and accurate representation of 3D objects. Augmented Reality in E-commerce allows customers to view products or experience services in their physical space before purchasing the required items. Current online shopping services only allow customers to see 2D images of the products they are buying. This type of experience is not personalized and sometimes leads to bad shopping choices choices; the customers find it difficult to shop only with a static image view available. Customers cannot accurately predict whether the product they purchase will fit their home environment. This results in a lot of people returning or exchanging the things their purchases. AR resolves these issues. Thus, a method has been proposed for adding a virtual object in the real world by just using a real-time camera. The main aim of this paper is to provide user visualization of high resolution E-commerce products in a real environment.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114247802","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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