Deep Learning for Sensor-based Human Activity Recognition

279 indexed citations

Abstract

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About

This paper, published in 2021, received 279 indexed citations. Written by Kaixuan Chen, Dalin Zhang, Lina Yao, Bin Guo, Zhiwen Yu and Yunhao Liu covering the research area of Computer Networks and Communications, Artificial Intelligence and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (206 citations), Artificial Intelligence (100 citations) and Biomedical Engineering (75 citations). Published in ACM Computing Surveys.

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Countries where authors are citing Deep Learning for Sensor-based Human Activity Recognition

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Citations

This map shows the geographic impact of Deep Learning for Sensor-based Human Activity Recognition. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Deep Learning for Sensor-based Human Activity Recognition with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deep Learning for Sensor-based Human Activity Recognition more than expected).

Fields of papers citing Deep Learning for Sensor-based Human Activity Recognition

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Deep Learning for Sensor-based Human Activity Recognition. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Deep Learning for Sensor-based Human Activity Recognition.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1145/3447744.

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