2022 International Conference on Edge Computing and Applications (ICECAA)最新文献_第4页

A Robust Deep Learning and Feature Fusion-based Multi-class Classification of Cervical Cells 基于鲁棒深度学习和特征融合的宫颈细胞多类分类

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936276

R. Madhukar, Rakesh Chandra Joshi, M. Dutta

{"title":"A Robust Deep Learning and Feature Fusion-based Multi-class Classification of Cervical Cells","authors":"R. Madhukar, Rakesh Chandra Joshi, M. Dutta","doi":"10.1109/ICECAA55415.2022.9936276","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936276","url":null,"abstract":"Cervical cancer is one of the prevalent and lethal diseases in women which can be prevented if routine screenings are conducted to find premalignant lesions at an initial stage to cure them. The pap-smear test is used for early detection but this is not much efficient because it is a time-consuming process and other manual screening methods give high human error rates and false-positive results. To overcome the classification of cervical cell problems, a deep learning-based automatic computer-aided diagnostic system has been developed using pap-smear images of cervical cells. This study is focused on different limitations in the classification of cervical cells and a deep learning-based feature fusion network is proposed in this work. The proposed network model has been tested on a publicly available CRIC searchable image dataset. The trained model with an accuracy of 96.07%, 93.30%, and 85.07% on an unseen test set images for 2-class, 3-class, and 6-class classification, respectively. The performance metrics supported the models' accuracy with improved outcomes as compared to the trained single network. The model includes features extracted from various networks, highly efficient feature extraction suitable for cervical cell image analysis and other biological applications.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426366","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

Cross Domain Movie Recommendation System using Personalized Preference Transfer 基于个性化偏好转移的跨域电影推荐系统

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936104

S. Soundariya, S. Manisekaran, S. Ramakrishnan, Aiswarya Ganesh, R. Keerthi

{"title":"Cross Domain Movie Recommendation System using Personalized Preference Transfer","authors":"S. Soundariya, S. Manisekaran, S. Ramakrishnan, Aiswarya Ganesh, R. Keerthi","doi":"10.1109/ICECAA55415.2022.9936104","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936104","url":null,"abstract":"Recommendation System has become more customized than ever. However, it suffers from cold start and data sparsity issues. Cross Domain Recommendation (CDR) has been proposed as a promising and feasible approach which yields recommendations in the destination domain based on the characteristic and personalized preferences of the users in the source domain. Since the fondness varies for each user, their taste bridge would also be different. Most of the well-known existing models make use of common preference bridge when it comes to transferring preferences for all the users in the system. Personalized Preference Transfer (PPT) for personalizing user preferences using Characteristic Encoder (CE) where user characteristic is mapped to initializing maps is pro-posed for cold start users and from books for warm start users. In this model, a Meta net-work with user attributes is used to attain the bridge preferences for individual users. The Deep Neural Network (DNN) which is a neural network model is used to provide optimized recommendations to the users. The accuracy and efficiency of personalized user preferences transfer is determined based on the comparisons from different models and train/test ratios, making use of two evaluation metrics MAE (Mean Absolute Error) and RMSD (Root Mean Squared Deviation).","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128056055","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

Data Acquisition and Image Augmentation using Adversarial Networks 使用对抗网络的数据采集和图像增强

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936265

U. Lathamaheswari, J. Jebathagam

{"title":"Data Acquisition and Image Augmentation using Adversarial Networks","authors":"U. Lathamaheswari, J. Jebathagam","doi":"10.1109/ICECAA55415.2022.9936265","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936265","url":null,"abstract":"It is possible to avoid challenges caused by overfitting, and the performance of machine learning algorithms can improve when there is a large amount of data. The improved training data diversity that is offered by data augmentation, which does not require the collection of fresh data, is beneficial to the algorithms that are used in machine learning. In this paper, we collect the data from the associated paddy leaf dataset, however, it is found that the collected data is insufficient for conducting the training and testing of a classifier. In order to increase the samples for training and testing to predict the leaf disease using a machine or a deep learning classifier, it is essential to increase the number of instances for efficient classification. In regards to this, the study uses Generative Adversarial Networks (GANs) to increase the images required for training and testing using image cropping, flipping, color transformation, rotation and noise injection on the collected datasets. The simulation is conducted in python for the generation of images from the input datasets and we store these augmented images for further processing.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128201717","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

Development of AI Intelligent Decision-Making System for Engineering Project Investment Cost Control based on Big Data Information Collection Algorithm 基于大数据信息采集算法的工程项目投资成本控制AI智能决策系统开发

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936347

Xiaoyan Xiong

引用次数: 0

Information Extraction and Sentence Ordering in Multi-Document Summarization using Preference Learning 基于偏好学习的多文档摘要信息提取与句子排序

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936218

Anuj Kumar, Atul Kumar Uttam

引用次数: 0

Rehabilitation Assessment of Lumbar Sports Injury based on Intelligent Analysis of MRI images 基于MRI图像智能分析的腰椎运动损伤康复评估

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936271

Bin Feng, Hang Dong, Wenbao Li

引用次数: 0

Application of Big Digital Media Data Compression Recognition Algorithm in Modern Art Design Training Intelligence 大数字媒体数据压缩识别算法在现代艺术设计训练智能中的应用

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936439

Youquan Liu, Wenhua Huang

引用次数: 0

Advanced Online Cheque Clearing System using Blockchain 使用区块链的高级网上支票结算系统

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936509

M.Keerthi Naga Saraswathi, B. Bharathi

引用次数: 0

Sentimental Analysis on Student Feedback using NLP & POS Tagging 用自然语言处理和词性标注对学生反馈的情感分析

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936569

N. R, Pallavi M S, Pramath. P. Harithas, V. Hegde

{"title":"Sentimental Analysis on Student Feedback using NLP & POS Tagging","authors":"N. R, Pallavi M S, Pramath. P. Harithas, V. Hegde","doi":"10.1109/ICECAA55415.2022.9936569","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936569","url":null,"abstract":"Sentiment analysis has been extensively used in a variety of fields in the previous decade, including business, social media, and education. The usage of sentiment analysis is rising, but it remains difficult, particularly in the education area, where the nature of the language utilized by pupils and a sizeable amount of information, dealing with their processing thoughts is a difficult task. Several studies of the literature illustrate the current state of sentiment analysis application which include sector from various perspectives and circumstances. In the teaching analysis system, the qualifier sentimental words for student feedback aren’t thought of the result of teaching analysis through student feedback isn’t displayed whether positive or negative opinion. To efficiently utilize sentimental analysis for the teaching system through student feedback, this paper proposes to analyze the scholar’s text feedback automatically using NLP and post-tagging based approach to conclude the extent of teaching work. Here, the main concentration is applying sentimental analysis for students’ feedback, collected through online mode. The use of ML and the NLP approach to examine the feelings of the students included in the text document is used for classification based on students’ comments to predict the polarity (positive/ negative). A total of 2200 student feedback are collected and analyzed, which results in 60 percentage positive and 40 percentage negative through Post Tagging.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"77 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134332023","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: 3

Application of the Multi-Perception Algorithm Platform of the Full-Chain Technology Innovation and Entrepreneurship to the Generation of Online Training Videos for Talent Cultivation 全链科技创新创业多感知算法平台在人才培养在线培训视频生成中的应用

2022 International Conference on Edge Computing and Applications (ICECAA) Pub Date : 2022-10-13 DOI: 10.1109/ICECAA55415.2022.9936369

Han Yan

引用次数: 0