2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)最新文献_第5页

Face Mask and Social Distancing Detection for Surveillance Systems 监测系统的口罩和社交距离检测

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452973

L.A. Rakhsith, B. Karthik, A. D, K. V, K. Anusha

{"title":"Face Mask and Social Distancing Detection for Surveillance Systems","authors":"L.A. Rakhsith, B. Karthik, A. D, K. V, K. Anusha","doi":"10.1109/ICOEI51242.2021.9452973","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452973","url":null,"abstract":"There is a huge panic among the people in recent times due to the spread of communicable diseases. People are in close vicinity to one another when in closed spaces like shops, restaurants, classrooms, etc. There is also a cause for worry in workplaces regarding the safety of the workplace. This paper discusses about two models which can be used to detect the distance between people to ensure social distancing and to detect if people are wearing a mask which can be implemented to follow safety measures. To implement these models deep learning techniques are used. For the social distancing model object detection is done to detect humans and this is done through the YOLOv3. For the mask detection model, the MobileNetV2 is the algorithm which is used for classification. This is used to detect if the people are wearing a mask. These two models can be used for the purpose of prevention against widely spreading diseases. For example, if the people of an organization have to request their customers to stay 6 feet apart or wear a mask in cases where the customers are not following the standard safety protocols, the people of the organization should go directly up to them and request for it. This increases the contact between people and at the same time increases the risk factor for the people working in that organization. When these models are implemented, it reduces unnecessary human contact while also ensuring to alert the customers if they break these protocols.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127128867","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}

引用次数: 4

Digital Eye Strain Detection System Based on SVM 基于SVM的数字眼疲劳检测系统

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453085

Ramandeep Kaur, Ankita Guleria

{"title":"Digital Eye Strain Detection System Based on SVM","authors":"Ramandeep Kaur, Ankita Guleria","doi":"10.1109/ICOEI51242.2021.9453085","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453085","url":null,"abstract":"Usage of digital devices especially smartphones significantly increased in the previous decade. Moreover, COVID pandemic has further shifted much of the work towards digital device assisted applications. In today's era, people across all ages are spending a lot of time in front of these devices. This also implies a surge in Digital Eye Strain cases, which is one of the emerging health issues. Researchers have linked this problem with symptoms such as dry eyes, altered blinking pattern, visual fatigue etc. Although the previous studies on facial features have already focused on blinking patterns, yawn detection and head movement, the proposed research work has concluded that other facial gestures comprising droopy eyes and decrease in glabellar length are also relevant features for this study to increase the accuracy. This paper tries to effectively detect when a user is under strain so that he or she can take timely precautions. A supervised method based on statistical features linked to suggested symptoms is proposed for classifying videos recorded in real time as user under strain using SVM. The main finding is an explicit feature set comprising of two newly proposed features along with four other apposite features derived from previous theoretical studies. The proposed system shows considerable increase in accuracy when tested on YawDD, the best possible dataset available for our use case.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128944218","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}

引用次数: 0

Covid19 tracking algorithm and conceptualization of an associated patient monitoring system covid - 19跟踪算法和相关患者监测系统的概念化

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452910

S. Varun, R. Nagaraj

引用次数: 1

Network information inheritance of traditional and migrant craftsmanship based on the background of big data 基于大数据背景下的传统与流动工艺的网络信息传承

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453048

Fang Ji, Yulong Xue

引用次数: 0

Securing Data by Detecting Multi Channel Attacks Using Deep Learning 通过使用深度学习检测多通道攻击来保护数据

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452921

A. Mary, Emmaneni Venkata Naga Sai Prem, Sri Hari Jujjavarapu, P. Asha

引用次数: 2

An In-Depth Look at the Images for Finding Information using Deep learning and Reverse Image Search 深入了解使用深度学习和反向图像搜索查找信息的图像

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452817

Y. V. Sai, Salman, T. Sasikala

{"title":"An In-Depth Look at the Images for Finding Information using Deep learning and Reverse Image Search","authors":"Y. V. Sai, Salman, T. Sasikala","doi":"10.1109/ICOEI51242.2021.9452817","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452817","url":null,"abstract":"An In-Depth look at images for finding information using deep learning and reverse image search explains that current technology necessitates a modern approach for extracting information from images. Generating a caption from an image may require computer vision and natural language processing concepts for generating the caption in a natural language like English etc. This paper attempts to show how more information can be generated from an image for further analysis of making some predictions. This project is able to detect the person's identity if a person's face is visible in the image as well as all about the image as to where it has taken resolution, and all other factors. The entire project will describe as much information as possible and utilize it for further analysis. For example, given a white lion image then the image may tell the output as “The white lion is a rare color mutation of the lion, specifically the Southern African lion.” or if an image contains a person as an anonymous then the output will be like “Name, Address and lot more”. It can give you complete information about an image, apart from the basic information and the EXIF data, it also shows other useful and in-depth data. There are some reasons that why you need to get information from a photo if a photo you saw that selling a product at a cheap price then we definitely may be interested to buy but wait that may be a scam or what if someone send you the friend request that is the real or fake person that also we have to be aware and what if you are going to meet with a wrong people if he used a fake photo last time with you and you are going to meet with the wrong guy.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130916419","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}

引用次数: 1

Integration of BIM and Data Optimization Technology Into the Online Guiding of Engineering Management in Colleges BIM与数据优化技术在高校工程管理在线指导中的集成

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452851

Shaoyun Yin, Hao Cheng, Tao Sun

引用次数: 0

A Design Approach for Performance Analysis of Infants Abnormality Using K Means Clustering 基于K均值聚类的婴儿异常性能分析设计方法

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452867

Rahul Agrawal, K. Jajulwar, Urvashi Agrawal

{"title":"A Design Approach for Performance Analysis of Infants Abnormality Using K Means Clustering","authors":"Rahul Agrawal, K. Jajulwar, Urvashi Agrawal","doi":"10.1109/ICOEI51242.2021.9452867","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452867","url":null,"abstract":"The common challenge observed in the early stages of pregnancy is the birth defect of infants. The key factors for this challenge are genetics and infection during pregnancy. According to GHO information, in 2015 about 4.5 million deaths occurred due to the sudden death syndrome and lack of nourishment of the fetus during pregnancy. One of the most important causes for abnormalities in infants is the bulge in their legs and abdomen. Bulge leads to many other problems and affect body functions such as brain, hand, and legs mostly in abdomen. In this paper, 117 images obtained from Beth Israel Deaconess Medical are taken for research purpose i.e., to identify the abnormalities in the fetal brain by using unsupervised learning algorithm. Proposed system is equipped to detect or classify the abnormalities of the fetus having gestational age from 14-38 weeks. Head region and abdomen region of the fetus is used for futher research analysis. Convex hull method is applied to the acquired images for performing image segmentation. The parameters like head diameter and abdomen circumference are used to incorporate feature extraction and followed by that k-means clustering algorithm is used to classify abnormalities in infants. The proposed system gives promising results for detecting the abnormalitiesof fetus and the accuracy is coming out to be 83.76% by using K-means clustering algorithm.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122547691","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}

引用次数: 15

Comparative Study on Telugu text Classification using Machine Learning and Deep Learning models 机器学习与深度学习模型在泰卢固语文本分类中的比较研究

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453040

Veerraju Gampala, Jaideep Vallapuneni, Pavan Kumar Ande, Ravindra Kumar Indurthi, N. Rajesh

{"title":"Comparative Study on Telugu text Classification using Machine Learning and Deep Learning models","authors":"Veerraju Gampala, Jaideep Vallapuneni, Pavan Kumar Ande, Ravindra Kumar Indurthi, N. Rajesh","doi":"10.1109/ICOEI51242.2021.9453040","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453040","url":null,"abstract":"Nowadays, many Telugu Language documents have become available in digital form in this information era. These documents should be grouped into a class based on their content for easy retrieval of these electronic data records. Text categorization is perhaps the crucial issue in information systems concerned with text records, owing to the increasing volume of information contained in digital form. Text categorization methods have been applied to Telugu text in order to derive valuable information and insights from unstructured Telugu text. Text categorization is the method of identifying a category or several categories from a set of predefined choices for a document. Indian languages are difficult to categories because they have a lot of morphology, a lot of different word forms, and a lot of different feature spaces. Since Telugu is morphologically rich and requires special algorithms to perform morphological analysis, there hasn't been much research done on it. To construct an organized and reduced-feature lexicon, the preprocessing methods which are designed specifically for Telugu language are applied to raw data. Significant pre-processing is required to construct accurate classification model Telugu text documents. In this paper, we compare the different machine learning and deep learning classifiers performance on the Telugu text such as Naïve Bayes, Support Vector Machine (SVM), and neural network classifier.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"515 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116214566","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}

引用次数: 4

Projection of Malignant Tumor of the Cervix using Machine Learning 宫颈恶性肿瘤的机器学习投影

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453044

P. A, G. S, Archith K, P. K

引用次数: 0