2021 the 5th International Conference on Information System and Data Mining最新文献

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MDNet: A Multi-image Input Real-Time Semantic Segmentation Model with Decoupled Supervision 一种具有解耦监督的多图像输入实时语义分割模型
2021 the 5th International Conference on Information System and Data Mining Pub Date : 2021-05-27 DOI: 10.1145/3471287.3471301
Yunze Wu
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引用次数: 0
A Survey on Mainstream Dimensions of Edge Computing 边缘计算主流维度综述
2021 the 5th International Conference on Information System and Data Mining Pub Date : 2021-05-27 DOI: 10.1145/3471287.3471295
Yuanda Wang, Haibo Wang, Shigang Chen, Ye Xia
{"title":"A Survey on Mainstream Dimensions of Edge Computing","authors":"Yuanda Wang, Haibo Wang, Shigang Chen, Ye Xia","doi":"10.1145/3471287.3471295","DOIUrl":"https://doi.org/10.1145/3471287.3471295","url":null,"abstract":"Driven by the booming of Internet of Things and 4G/5G communications, an increasingly large number of edge devices, e.g., sensors and cell phones, are continuously producing data service requests, which should be processed in high quality. Recent years have seen a paradigm shift from centralized cloud computing toward edge computing. Edge computing is a distributed computing paradigm that utilizes computing and storage resources of edge devices. Compared with traditional cloud computing, edge computing migrates data computation and storage to the edge devices. Recently many technical breakthroughs have been made in edge computing. This survey reviews existing research on edge computing with a focus on the three mainstream dimensions: resource allocation, data fusion and security. We present specific techniques of the three dimensions and how they can contribute to the improvement of edge computing. Emerging and prospective application fields that would benefit from edge computing are also discussed.","PeriodicalId":306474,"journal":{"name":"2021 the 5th International Conference on Information System and Data Mining","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123915074","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: 2
Automated Dataset Amplification and its Application to Small Dataset Object Detection Transfer Learning 自动数据集放大及其在小数据集目标检测中的应用
2021 the 5th International Conference on Information System and Data Mining Pub Date : 2021-05-27 DOI: 10.1145/3471287.3471305
Muhammad R. Abid, Riley Kiefer
{"title":"Automated Dataset Amplification and its Application to Small Dataset Object Detection Transfer Learning","authors":"Muhammad R. Abid, Riley Kiefer","doi":"10.1145/3471287.3471305","DOIUrl":"https://doi.org/10.1145/3471287.3471305","url":null,"abstract":"∗Object detection is a core process for many image processing applications. Using the YoloV3 deep learning approach to object detection, which is trained on a fixed set of objects, transfer learning is applied to learn the features of novel construction objects. Transfer learning typically requires a large dataset of both images and labels, and labeling image data can take a long time. This paper will introduce several preprocessing pipeline approaches as a means of data amplification and data augmentation to enhance a small dataset using a combination of the following transformations: rotation, scaling, flipping, and grayscale conversion. A construction safety helmet detection model is trained using various experimental data preprocessing pipelines and the results are presented.","PeriodicalId":306474,"journal":{"name":"2021 the 5th International Conference on Information System and Data Mining","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129008760","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
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