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2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)最新文献

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Covid-19 Vaccine Tweets Sentiment Analysis and Topic Modelling for Public Opinion Mining 面向舆论挖掘的Covid-19疫苗推文情感分析与话题建模
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9671000
Trisha Baldha, Malvi Mungalpara, Priyanka Goradia, Santosh Bharti
{"title":"Covid-19 Vaccine Tweets Sentiment Analysis and Topic Modelling for Public Opinion Mining","authors":"Trisha Baldha, Malvi Mungalpara, Priyanka Goradia, Santosh Bharti","doi":"10.1109/aimv53313.2021.9671000","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9671000","url":null,"abstract":"The world is facing the major crisis in the form of coronavirus pandemic. Since it’s been more than a year of Covid-19 pandemic, there has been a significant call in social media regarding the requirement and feasibility for COVID-19 Vaccine. This paper aims at analyzing tweets related to Covid-19 Vaccine, determining the sentiments about vaccination and extracting the significant topics. We performed multi-class sentiment analysis, steps comprising of pre-processing followed by training three different classification models: Gaussian Naïve Bayes, Support Vector Machine and LSTM. Results of the model obtained was one the three (Positive, Negative, Neutral) sentiment. Based on the outcomes, accuracy and F1- scores were computed to draw comparison between distinct models. Topic Modeling was performed using LDA on the combined tweets dataset to derive top seven important topics. In addition, Exploratory Data Analysis was also performed on dataset consisting of Vaccination Progress worldwide to bring out popularity of vaccines.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127896224","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
AIMV 2021 Table of Contents AIMV 2021目录
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670962
{"title":"AIMV 2021 Table of Contents","authors":"","doi":"10.1109/aimv53313.2021.9670962","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670962","url":null,"abstract":"","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131890117","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
Inner Voice - An Effortless Way Of Communication For The Physically Challenged Deaf & Mute People 内心的声音-一种毫不费力的沟通方式，为残疾聋哑人
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670911
Vaishnavi Jamdar, Yogita Garje, Trupti Khedekar, Sneha Waghmare, M. Dhore
{"title":"Inner Voice - An Effortless Way Of Communication For The Physically Challenged Deaf & Mute People","authors":"Vaishnavi Jamdar, Yogita Garje, Trupti Khedekar, Sneha Waghmare, M. Dhore","doi":"10.1109/aimv53313.2021.9670911","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670911","url":null,"abstract":"Communication, which is the basis of human development, often tends to be an obstacle for those physically challenged people that are unable to speak and articulate their thoughts. During a conversation between a hearing and speech impaired person and a normal person the difficulty of communication hampers the comfort level. Inner voice works as a daily communication tool for those that have trouble speaking. For better communication, it allows users to voice their needs and feelings quickly and simply in a picture-based communication app. It is a portable, fitted, and easy-to- use communication tool designed to reduce the communication gap.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116679054","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
Internet of Things Security: Attacks, Solutions, Strengths and Limitations 物联网安全:攻击、解决方案、优势和局限性
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670971
Sanjit Kumar, K. A. Kumar, Rahul Raman
{"title":"Internet of Things Security: Attacks, Solutions, Strengths and Limitations","authors":"Sanjit Kumar, K. A. Kumar, Rahul Raman","doi":"10.1109/aimv53313.2021.9670971","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670971","url":null,"abstract":"Internet of Things (IoT) has become an intangible part of regular life over the past decade. There are innovations in new wearable smart devices to various domestic appliances on a very regular basis. But IoT devices owing to the intricacy they have with our daily lives also usually store a large amount of sensitive data making IoT devices target large information security attacks. In this article, we have attempted to accumulate various security threats that IoT devices can face and the current landscape of research on countermeasures for the same. Later, we have presented a contrast to analyse the difference between major security frameworks and their efficacy. The research is further concluded on examination of potential research dimensions, scope, and related challenges in multiple research aspects.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122545705","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
Emotionally relevant background music generation for audiobooks 有声读物的情感相关背景音乐生成
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670959
D. Lôbo, Jenny Dcruz, Leander Fernandes, Smita Deulkar, Priya Karunakaran
{"title":"Emotionally relevant background music generation for audiobooks","authors":"D. Lôbo, Jenny Dcruz, Leander Fernandes, Smita Deulkar, Priya Karunakaran","doi":"10.1109/aimv53313.2021.9670959","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670959","url":null,"abstract":"Over the past few years, the number of people listening to audiobooks has only increased. There is no doubt that audiobooks are a popular source of entertainment. However, one may enjoy the narration more if it came along with some background music which is rarely the case as audiobook producers prefer to avoid paying for this premium service due to its cost. This affects the experience that the author is trying to create for the listener with regard to the story. To help tackle this issue, we propose a system that takes an audiobook and generates relevant background music for it based on the emotions predicted by our hybrid emotion analysis model.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130271383","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
A Survey on Machine Learning in Lithography 光刻中的机器学习研究综述
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670977
Mansi Phute, Aditi Sahastrabudhe, Sameer Pimparkhede, Shubham Potphode, Kshitij Rengade, Swati Shilaskar
{"title":"A Survey on Machine Learning in Lithography","authors":"Mansi Phute, Aditi Sahastrabudhe, Sameer Pimparkhede, Shubham Potphode, Kshitij Rengade, Swati Shilaskar","doi":"10.1109/aimv53313.2021.9670977","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670977","url":null,"abstract":"Lithography is the process of transferring the geometric patterns from the masks to the resist material on the semiconductor. It is a very important part of VLSI fabrication that is critical when it comes to the efficient functioning of circuits. Many state-of-the-art methods use Machine Learning (ML) to identify lithography patterns that can cause issues in the future as these algorithms can predict defects in patterns which the machine has not encountered before. This paper focuses on the need for Machine Learning in the lithography process, and the various algorithms used like Support Vector Machines (SVM), Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN). There are multiple applications including Hotspot detection, Optical Proximity Correction (OPC), Sub Resolution Assist Feature (SRAF), Phase Shift Masks (PSM), and Resist Modelling. The major issue faced by Machine Learning algorithms is that of false positives. It can be reduced by utilizing the Gaussian process after initial detection.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128249643","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: 2
Intelligent System for Detecting Intrusion with Feature Bagging 基于特征装袋的智能入侵检测系统
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670940
Debabrata Swain, Naresh Chillur, Sagar Patel, Amol Bhilare
{"title":"Intelligent System for Detecting Intrusion with Feature Bagging","authors":"Debabrata Swain, Naresh Chillur, Sagar Patel, Amol Bhilare","doi":"10.1109/aimv53313.2021.9670940","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670940","url":null,"abstract":"Cyber-security has received considerable attention as a result of individuals and businesses’ enormous impact on the Internet and their concern about the security and privacy of their online activities. Due to this, predicting cyberattacks with machine learning has become crucial as the number of attacks has risen dramatically as a result of attackers’ stealth and sophistication. To maintain situational awareness and achieve defense in depth, collecting cyber threat intelligence requires the use of machine learning for threat prediction. With the increasing use of technology, intrusion detection has become a flourishing field of study. It monitors and alerts users to their typical (or) anomalous behavior. IDS is a nonlinear and challenging task that entails analyzing network traffic data. The purpose of this article is to examine the potential of employing machine learning approaches to forecast malware attacks. The objective is to foresee the types of network attacks that may occur. To demonstrate our work’s usefulness, we employed a random forest approach to learn the assessment dataset. This is where the random forest comes in handy.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126693365","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
Deep Convolutional Neural Networks for Scene Understanding: A Study of Semantic Segmentation Models 用于场景理解的深度卷积神经网络:语义分割模型的研究
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670955
Malvi Mungalpara, Priyanka Goradia, Trisha Baldha, Yanvi Soni
{"title":"Deep Convolutional Neural Networks for Scene Understanding: A Study of Semantic Segmentation Models","authors":"Malvi Mungalpara, Priyanka Goradia, Trisha Baldha, Yanvi Soni","doi":"10.1109/aimv53313.2021.9670955","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670955","url":null,"abstract":"Semantic Image Segmentation for autonomous cars is gaining a lot of popularity in recent times with researchers trying to improvise the model as much as possible. In this paper, we have compared three models, UNet, VGG16_FCN and ResNet50_FCN, which are used for semantic image segmentation. We have trained and tested these models on the cityscape dataset where the models classify each pixel of the image into various classes. Results show that the class-wise accuracy of ResNet50_FCN is more than the other two models. We have also plotted IoU graphs for each model and we found out that ResNet50_FCN and VGG16_FCN have much better scores than the UNet model. Based on these results, we have shown that ResNet50_FCN outperforms the other two models for the case of semantic segmentation for scene understanding.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125299071","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: 2
An Examination Application For Blind Students With Subjective Answer Evaluator 基于主观答案评价者的盲人考试申请
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9670936
Deepali J. Joshi, Ajinkya Kulkarni, Manasi More, Riya Pande, Siddharth Patil, Nikhil Saini
{"title":"An Examination Application For Blind Students With Subjective Answer Evaluator","authors":"Deepali J. Joshi, Ajinkya Kulkarni, Manasi More, Riya Pande, Siddharth Patil, Nikhil Saini","doi":"10.1109/aimv53313.2021.9670936","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9670936","url":null,"abstract":"We present in this paper an examination application for blind students with a subjective answer evaluator. In the present scenario, Blind students need a volunteer to give exams, but we have proposed a solution to that by developing a completely voice-controlled website that also records answers given by the students. This will help increase the number of literates who are visually impaired giving as they can independently give exams. The current way of checking subjective answers is adverse. Whenever a human being evaluates papers, the quality is affected by emotion. In this paper, we are testing four different models for subjective answers evaluation using machine language. These models include Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbours. After testing Random Forest proved to be the best giving 83%accuracy.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132415230","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
A Machine Learning Approach to Thyroid Carcinoma Prediction 甲状腺癌预测的机器学习方法
2021 International Conference on Artificial Intelligence and Machine Vision (AIMV) Pub Date : 2021-09-24 DOI: 10.1109/aimv53313.2021.9671012
Shanu Verma, R. Popli, H. Kumar
{"title":"A Machine Learning Approach to Thyroid Carcinoma Prediction","authors":"Shanu Verma, R. Popli, H. Kumar","doi":"10.1109/aimv53313.2021.9671012","DOIUrl":"https://doi.org/10.1109/aimv53313.2021.9671012","url":null,"abstract":"A malignant tumor cell, such as a disorder, forms in the thyroid gland tissue, eventually leading to thyroid cancer. When malignant cancerous cells alter structure or change, thyroid cancer emerges. Mutated cells begin to develop in thyroid and eventually form a tumor if there are enough of cells. Thyroid cancer is one of the most curable forms of cancer if diagnosed early. The goal of this research is to use machine learning algorithms to analyse and forecast thyroid carcinoma based on the year, gender, and age group. The proposed research is a descriptive cross-sectional study that uses evidence in the form of data from the World Bank for Cancer on thyroid carcinoma incidence. The purpose of this research is to understand the global effects of thyroid cancer by gender and age. In the future, this paper will use a machine learning algorithm to predict accuracy on a minimal number of specific thyroid carcinoma attributes.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"1 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125602532","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
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