International Journal of Machine Learning and Networked Collaborative Engineering最新文献

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Improving the performance of one-shot face recognition by using data augmentation 利用数据增强技术提高一次性人脸识别的性能
International Journal of Machine Learning and Networked Collaborative Engineering Pub Date : 1900-01-01 DOI: 10.30991/ijmlnce.2020v04i04.003
Nguyen Thanh Trong, Luong Gia Kien, T. T. T. Tran, H. Duong, Tran Van Hoa, Thoai Nam
{"title":"Improving the performance of one-shot face recognition by using data augmentation","authors":"Nguyen Thanh Trong, Luong Gia Kien, T. T. T. Tran, H. Duong, Tran Van Hoa, Thoai Nam","doi":"10.30991/ijmlnce.2020v04i04.003","DOIUrl":"https://doi.org/10.30991/ijmlnce.2020v04i04.003","url":null,"abstract":"For a past few years, the revolution of deep learning techniques has emerged and launched several state-of-the-art models, for instance, the breakthroughs of DeepFace and DeepID to face recognition in 2014. The face recognition in CCTV systems commonly encounters a few obstacles coming from practical conditions, such as ambient light, the diverse positions and angles of cameras, face masks, face poses, and so on. In addition, people who are monitored by the CCTV systems lack photos and typically have only one photo. These problems lead to face recognition reported with unstable performance and difficult to be successfully used in practice. To tackle these problems, this paper proposes an approach, namely ISE, to face augmentation which interpolates multiple samples from an original photo. Particularly, the samples produced by ISE contain real characteristics of cameras in the CCTV systems. By practically deploying a CCTV system at the Bach Khoa Dormitory, ISE indicates that it can boost the performance of face recognition up from 72%, 46% to 84%, 64% in daytime and day-and-nighttime, respectively.","PeriodicalId":338210,"journal":{"name":"International Journal of Machine Learning and Networked Collaborative Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131904582","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
E-Recruitment In HR Consultants via E-Technology 通过电子技术实现人力资源顾问的电子招聘
International Journal of Machine Learning and Networked Collaborative Engineering Pub Date : 1900-01-01 DOI: 10.30991/ijmlnce.2020v04i03.003
Puja Roshani, Shivani Agarwal
{"title":"E-Recruitment In HR Consultants via E-Technology","authors":"Puja Roshani, Shivani Agarwal","doi":"10.30991/ijmlnce.2020v04i03.003","DOIUrl":"https://doi.org/10.30991/ijmlnce.2020v04i03.003","url":null,"abstract":"Human Resources consulting is that branch of management which concentrates on the process of efficiently utilizing employees to attain the objectives of the organization. A proficient and effective HR consultant can help the business to become productive by guiding company in a varied array of matters. This study was oriented to go through the usefulness of E-recruitment or online recruitment. The study specially aimed to govern the recruitment via electronic medium. It also aims to understand how major job portals perform their operations and provide services. It is found that majority of the respondents agreed that number of successful candidates, cost per hire, time taken to close position and candidate and employer satisfaction impact the e-recruitment.","PeriodicalId":338210,"journal":{"name":"International Journal of Machine Learning and Networked Collaborative Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130667823","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
IoT and AI-based Plant Monitoring System 基于物联网和人工智能的工厂监控系统
International Journal of Machine Learning and Networked Collaborative Engineering Pub Date : 1900-01-01 DOI: 10.30991/ijmlnce.2020v04i03.005
Bhuvan Puri
{"title":"IoT and AI-based Plant Monitoring System","authors":"Bhuvan Puri","doi":"10.30991/ijmlnce.2020v04i03.005","DOIUrl":"https://doi.org/10.30991/ijmlnce.2020v04i03.005","url":null,"abstract":"Plants plays a vital role in the environment because it provides the health support through absorbing the carbon dioxide and releasing the oxygen to the atmosphere. Although, it required to maintain the proper plant growth and health as well as provide the appropriate monitoring. To overcome these concerns, an Artificial Intelligence (AI) and Internet of Things (IoT) based solution is proposed to monitor the plant’s growth and health. This study demonstrates the real-time monitoring of the plants via environmental sensors such as DHT 11 and soil moisture sensors. Real-time values stored in the cloud server and applied the machine learning models to predict the plant’s growth. The Statistical parameters such as RMSE, MAE are used to analyze the resulting outcome from the system.","PeriodicalId":338210,"journal":{"name":"International Journal of Machine Learning and Networked Collaborative Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122831705","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
Novel Approach for Analysis of Face Recognition using Stereo Matching Algorithm 基于立体匹配算法的人脸识别分析新方法
International Journal of Machine Learning and Networked Collaborative Engineering Pub Date : 1900-01-01 DOI: 10.30991/ijmlnce.2020v04i03.001
Praneesh M Baby
{"title":"Novel Approach for Analysis of Face Recognition using Stereo Matching Algorithm","authors":"Praneesh M Baby","doi":"10.30991/ijmlnce.2020v04i03.001","DOIUrl":"https://doi.org/10.30991/ijmlnce.2020v04i03.001","url":null,"abstract":"This paper depicts a face acknowledgment structure that is equipped for preparing pictures across posture and enlightenment. The primary goal of this paper is to manufacture programmed face acknowledgment frameworks. This paper comprises of three primary segments of face acknowledgment structure. The principal segment is to construct the exhibition pictures of appearances alongside three milestone focuses. The subsequent segment bargains the enlightenment variety. The last segment handles the posture variety. The coordinating strategy of sound system handles the posture and articulation variety issues.","PeriodicalId":338210,"journal":{"name":"International Journal of Machine Learning and Networked Collaborative Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132094957","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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