{"title":"使用机器学习模型的视觉问题生成回答(VQG-VQA)","authors":"Atul Kachare, M. Kalla, Ashutosh Gupta","doi":"10.37394/23202.2023.22.67","DOIUrl":null,"url":null,"abstract":"Presented automated visual question-answer system generates graphics-based question-answer pairs. The system consists of the Visual Query Generation (VQG) and Visual Question Answer (VQA) modules. VQG generates questions based on visual cues, and VQA provides matching answers to the VQG modules. VQG system generates questions using LSTM and VGG19 model, training parameters, and predicting words with the highest probability for output. VQA uses VGG-19 convolutional neural network for image encoding, embedding, and multilayer perceptron for high-quality responses. The proposed system reduces the need for human annotation and thus supports the traditional education sector by significantly reducing the human intervention required to generate text queries. The system can be used in interactive interfaces to help young children learn.","PeriodicalId":39422,"journal":{"name":"WSEAS Transactions on Systems and Control","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visual Question Generation Answering (VQG-VQA) using Machine Learning Models\",\"authors\":\"Atul Kachare, M. Kalla, Ashutosh Gupta\",\"doi\":\"10.37394/23202.2023.22.67\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Presented automated visual question-answer system generates graphics-based question-answer pairs. The system consists of the Visual Query Generation (VQG) and Visual Question Answer (VQA) modules. VQG generates questions based on visual cues, and VQA provides matching answers to the VQG modules. VQG system generates questions using LSTM and VGG19 model, training parameters, and predicting words with the highest probability for output. VQA uses VGG-19 convolutional neural network for image encoding, embedding, and multilayer perceptron for high-quality responses. The proposed system reduces the need for human annotation and thus supports the traditional education sector by significantly reducing the human intervention required to generate text queries. The system can be used in interactive interfaces to help young children learn.\",\"PeriodicalId\":39422,\"journal\":{\"name\":\"WSEAS Transactions on Systems and Control\",\"volume\":\"20 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"WSEAS Transactions on Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37394/23202.2023.22.67\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"WSEAS Transactions on Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/23202.2023.22.67","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Visual Question Generation Answering (VQG-VQA) using Machine Learning Models
Presented automated visual question-answer system generates graphics-based question-answer pairs. The system consists of the Visual Query Generation (VQG) and Visual Question Answer (VQA) modules. VQG generates questions based on visual cues, and VQA provides matching answers to the VQG modules. VQG system generates questions using LSTM and VGG19 model, training parameters, and predicting words with the highest probability for output. VQA uses VGG-19 convolutional neural network for image encoding, embedding, and multilayer perceptron for high-quality responses. The proposed system reduces the need for human annotation and thus supports the traditional education sector by significantly reducing the human intervention required to generate text queries. The system can be used in interactive interfaces to help young children learn.
期刊介绍:
WSEAS Transactions on Systems and Control publishes original research papers relating to systems theory and automatic control. We aim to bring important work to a wide international audience and therefore only publish papers of exceptional scientific value that advance our understanding of these particular areas. The research presented must transcend the limits of case studies, while both experimental and theoretical studies are accepted. It is a multi-disciplinary journal and therefore its content mirrors the diverse interests and approaches of scholars involved with systems theory, dynamical systems, linear and non-linear control, intelligent control, robotics and related areas. We also welcome scholarly contributions from officials with government agencies, international agencies, and non-governmental organizations.