2021 IEEE Pune Section International Conference (PuneCon)最新文献

{"title":"Interpretation of Hand Spelled Banking Helpdesk Terms for Deaf and Dumb Using Deep Learning","authors":"Aditi Chavan, Jayshree Ghorpade-aher, Aakriti Bhat, Aniket Raj, Shubham Mishra","doi":"10.1109/punecon52575.2021.9686514","DOIUrl":"https://doi.org/10.1109/punecon52575.2021.9686514","url":null,"abstract":"The hand sign language uses visual-manual modality to share a certain message. Specially abled people having hearing and speaking disabilities interact more naturally in hand sign language rather than verbal language. According to one of the Census study, 2.21% out of 121 crore population in India are ‘disabled’, out of which 19% are having a hearing disability and 7% are having speech disability. Since everyone cannot communicate in sign language as it is a lesser-known language, it often leads to communication gap. So, the automated Sign Language Interpreter (SLI) helps to meet this communication gap as a manual sign language translator is not a convenient option because of its privacy issues and lack of availability. This paper proposes an Indian Hand Sign Language Interpreter which operates upon a vision-based approach that uses Machine Learning and Deep Learning techniques to locate the hand gesture region accurately for extracting the features and finally interpreting the respective meaning. The experimentation for performance metrics such as accuracy and loss using various activation functions helped to analyzed the performance of the model. The system successfully identifies a number of hand spelled words and thus eases the communication among people.","PeriodicalId":154406,"journal":{"name":"2021 IEEE Pune Section International Conference (PuneCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122274153","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}

{"title":"Multimodal Sentiment Analysis: Review, Application Domains and Future Directions","authors":"Ankita Gandhi, K. Adhvaryu, Vidhi Khanduja","doi":"10.1109/punecon52575.2021.9686504","DOIUrl":"https://doi.org/10.1109/punecon52575.2021.9686504","url":null,"abstract":"In this information age, opinion mining which is also known as sentiment analysis turns up to be the most important task in the field of natural language processing. Previous literature in area of sentiment analysis which mostly focused on single modality that is on textual data. Almost all the latest advancement in the sentiment analysis are using textual dataset and resources only. With the invent of internet which increases the use of social media, people are using vlogs, videos, pictures, audios, emojis and microblogs to represent their opinions on different web platforms. In this new media age, every day 720k hours of videos are uploaded on alone Youtube only. We have number of such platforms like YouTube. In the classical methods other modalities’ expressiveness is overlooked and thus these methods fail to generate accurate results. Numerous commercial applications used the aggregation of sentiments and opinions of individuals by anticipating large population. Thus, it is highly necessary that the diverse modalities from the raw data available from the internet should be utilized to mine opinions and identify sentiments. Varied data (i.e., text, speech, visual and code-mixed data) available over internet is integrated by Multimodal Sentiment Analysis. Multimodality refers to more than one modality like bimodal which uses any two modalities or trimodal which uses all the three modalities. Each modality offers its own exclusive features and can be collectively used to mine their positive or negative sentiments, opinions or responses about the entity. The latest development in multimodal sentiment analysis is that the diverse modalities i.e., audio, visual and textual are fused to generate better accuracy. Also, language and culture independent and speaker independent models can be generated. In this survey, we have defined various fusion techniques for sentiment analysis using multiple modalities, characteristics, features for multimodal sentiment analysis. This paper gives an outline of latest approaches used for multimodal sentiment analysis and various application domains in the field of multimodal Sentiment analysis using traditional methods as well as various deep learning methods. It also describes emerging areas of research in sentiment analysis using multimodal data.","PeriodicalId":154406,"journal":{"name":"2021 IEEE Pune Section International Conference (PuneCon)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121696165","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}

{"title":"Study of Quantum Annealing and the type of related applications","authors":"A. Venugopalan, R. K. Karishmah, R. Pillai, D. Sreedev, V. Balachandran, P. Bhattacharjee","doi":"10.1109/punecon52575.2021.9686503","DOIUrl":"https://doi.org/10.1109/punecon52575.2021.9686503","url":null,"abstract":"Most of the modern day computations are considered as an NP-hard like solving a puzzle or traveling salesman problem. Over the decades, engineers are exploring for many approaches of solution, out of which Quantum Annealing has depicted the efficacy. In this paper, we do a review study of Quantum Annealing (i.e., an approach to find the global mini-mum of a particular function that can provide better heuristics for the NP-hard optimization problem) and discussed briefly about quantum computers. Not only that, we also showcase few applications of quantum annealing which include scheduling problem, lung cancer detection, coherence in quantum annealer, and clustering.","PeriodicalId":154406,"journal":{"name":"2021 IEEE Pune Section International Conference (PuneCon)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133202551","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}