International Journal of Next-Generation Computing最新文献_第5页

Detection of Deepfake Video Using Residual Neural Network and Long Short-Term Memory 基于残差神经网络和长短期记忆的深度假视频检测

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International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1046

A. Karandikar, Yogesh Thakare, O. Sah, R. K. Sah, S. Nafde, S. Kumar

引用次数: 0

Facial Emotion Recognition through Neural Networks 基于神经网络的面部情绪识别

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International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1045

Abhijeet R. Raipurkar, Pravesh Dholwani, Atharva Pandhare, Rishabh Mittal, Aniket Tawani

{"title":"Facial Emotion Recognition through Neural Networks","authors":"Abhijeet R. Raipurkar, Pravesh Dholwani, Atharva Pandhare, Rishabh Mittal, Aniket Tawani","doi":"10.47164/ijngc.v14i1.1045","DOIUrl":"https://doi.org/10.47164/ijngc.v14i1.1045","url":null,"abstract":"Humans often express themselves through facial expressions. Deep learning techniques are used as an efficient system application process in research on the advancement of artificial intelligence technology in human-computer interactions. As an illustration, let’s say someone tries to communicate by using facial expressions. Some people who see it occasionally cannot foresee the expression or emotion it may evoke. Psychology includes study and evaluation of inferences in interpreting a person’s or group of people’s emotions when interacting in order to recognize emotions or facial expressions. Indeed, a convolutional neural networks (CNN) model may be learned to assess images and recognize facial expressions. This study suggests developing a system that can classify and forecast facial emotions using feature extraction and real-time Convolution Neural Network (CNN) technology from the OpenCV library. We have chosen FER 2013 Dataset as the main dataset for our study. Face detection, extraction of facial features, and facial emotion categorization are the three key procedures that make up the research that was implemented.","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"23 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73655756","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

Dynamic Microservice based scalable approach to list product deals 基于动态微服务的可伸缩方法来列出产品交易

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1042

Abhijeet R. Raipurkar, Pratik K. Agrawal, Radha Malichkar, Snehal Mopkar, Chetan Pardhi, Saiyyed Khhizr Aalam

{"title":"Dynamic Microservice based scalable approach to list product deals","authors":"Abhijeet R. Raipurkar, Pratik K. Agrawal, Radha Malichkar, Snehal Mopkar, Chetan Pardhi, Saiyyed Khhizr Aalam","doi":"10.47164/ijngc.v14i1.1042","DOIUrl":"https://doi.org/10.47164/ijngc.v14i1.1042","url":null,"abstract":"Customers always have to compare product prices and offers across several websites when they go to purchase a specific item. The solution seeks to address the fore mentioned issue. The comparison that Google Search now offers is focused more on text search than anything else. The pricing and any available coupons or discounts on that website are not listed. This paper proposes a solution- a price-deals-lister, a microservice based website which scrapes the various e-commerce websites and get the deals available, stores them in database and later the request processor unit will take the data from the database according to the user’s request and show it to the user. Customers and retailers alike will benefit from this initiative because it allows them to quickly and easily access all the data with just one click. Anyone can access the website and compare the offers found on other e-commerce websites. In view of the Market analysis, Shopkeepers can use a website to verify the current market price of a product, especially retailers that must offer their goods with tight margins. After that, they can raisethe product’s price in their store and sell it for a fair amount to make a profit. Shop owners can learn about various lucrative offers that are currently being offered for a specific product and utilize that knowledge to better serve their customers. Producers can research the products that consumers are most interested in and concentrate on making those products. Additionally, by providing the finest deals to the clients, they might consider various strategies for increasing the profitability of the products.","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"114 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88137059","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

Optimised Cluster-based Approach for Healthcare Data Analytics 优化的基于集群的医疗数据分析方法

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1011

Amol Bhopale, Sanskar Zanwar, Aarya Balpande, Jaweria Kazi

引用次数: 0

PlagCheck: An efficient way to identify Plagiarism using BERT PlagCheck:使用BERT识别抄袭的有效方法

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1030

Kanak Kalyani, Abhiyant Gwalani, Varun Kalbhore, Shreya Rai

引用次数: 0

Novel Study on Localization in Scene Text Detection 场景文本检测中定位的新研究

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1037

P. Sonsare, Rushabh Jain, Rutuj Runwal, Kunal Dave, Ashutosh Banode

{"title":"Novel Study on Localization in Scene Text Detection","authors":"P. Sonsare, Rushabh Jain, Rutuj Runwal, Kunal Dave, Ashutosh Banode","doi":"10.47164/ijngc.v14i1.1037","DOIUrl":"https://doi.org/10.47164/ijngc.v14i1.1037","url":null,"abstract":"Scene text detection has been one of the most important topics for research in computer vision. With constant development and rise in deep learning, computer vision technology has undergone an impactful transformation. In the era before deep learning, there existed algorithms and technologies for scene text detection, but the performance was mediocre. In recent years, deep learning technology has remarkably transformed scene text detection. Researchers have witnessed notable advancements in the approach, methodology, and overall performance of the newly discovered techniques. In this paper, the predominant focus is on summarizing and analysing the significant progress in scene text detection through deep learning. This paper covers an introduction to scene text detection, steps to perform scene text recognition and detection, technique before deep-learning, recent techniques and their insights, some results, and an overview by comparing the algorithms. We will also emphasize the criteria that make a search algorithm a good choice for performing scene text detection and recognition, the notable differences incorporated by deep learning, and analyse the drawbacks of the techniques used before deep learning. This paper would be helpful to understand the key differences that have changed this field and also some remaining challenges.","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"27 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72928007","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

Automatic Detection of Indian Currency Denominations using Deep Learning 使用深度学习的印度货币面额自动检测

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1028

Yash Patel, Ramakant Chhangani, Sarang Deshpande, Ramchand Hablani, Sweta Jain

{"title":"Automatic Detection of Indian Currency Denominations using Deep Learning","authors":"Yash Patel, Ramakant Chhangani, Sarang Deshpande, Ramchand Hablani, Sweta Jain","doi":"10.47164/ijngc.v14i1.1028","DOIUrl":"https://doi.org/10.47164/ijngc.v14i1.1028","url":null,"abstract":"Identification of the denomination of the currency note to pay physically without UPI is the first step of paying to the seller by the consumer. In this project, we have proposed an approach to detect denominations of Indian currency using Convolutional Neural Networks. Computer Vision and object detection is an area of great interest for research in today’s world. It has several applications like detection of defects in machinery, intruder detection, computer vision for code and character recognition among many others. Through the work we have done, we explored something that could be of great help to people in day-to-day life. In this project we have tried to investigate the approaches to detect currency denominations using Convolutional Neural Networks. The objective is to build a model that would be able to detect Indian currency denominations efficiently. Typically the model will be useful for people with vision impairment. The experimental results show that the use of Convolutional Neural Networks is a good way and the model can further be improved if it is trained in such a way that it could also identify the regions of interest.","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"14 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78547052","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 Novel Approach to Detect Brain Tumor Using CNN model of Deep Learning 一种基于CNN深度学习模型的脑肿瘤检测方法

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1041

P. Pardhi, Navya Verma, Nikunj Loya, Kartik Agrawal

引用次数: 0

Classification of Handwritten Digits on the web using Deep Learning 使用深度学习对网络上手写数字进行分类

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International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1003

Rutuj Runwal, Shrawan J Purve, Mohit Chandak

引用次数: 0

Detection of Pneumonia Using Deep Learning 利用深度学习检测肺炎

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International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI: 10.47164/ijngc.v14i1.1023

Nishant Borkar, Atharva Zararia, Riddhi Gangbhoj, Prashant Kumar, Vaishnavi Bhaiyya

引用次数: 0