Deep Learning for Sensor-Based Activity Recognition: Recent Trends-Reference-Cited by-同舟云学术

Deep Learning for Sensor-Based Activity Recognition: Recent Trends

Published:2020-07-31 Issue: Volume: Page:149-173
ISSN:1868-4394
Container-title:IoT Sensor-Based Activity Recognition
language:
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Author:

Ahad Md Atiqur Rahman,Antar Anindya Das,Ahmed Masud

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-51379-5_9

Reference117 articles.

1. Antar, A.D., Ahad, M.A.R., Shahid, O.: Vision-based action understanding for assistive healthcare: a short review. In: IEEE CVPR workshop (2019)

2. Ahad, M.A.R.: Vision and sensor based human activity recognition: Challenges ahead (2020)

3. Antar, A.D., Ahmed, M., Ahad, M.A.R.: Challenges in sensor-based human activity recognition and a comparative analysis of benchmark datasets: a review. In: 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), pp. 134–139. IEEE (2019)

4. Ahad, M.A.R.: Motion History Images for Action Recognition and Understanding. Springer Science & Business Media, Berlin (2012)

5. Ahad, M.A.R.: Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding, vol. 5. Springer Science & Business Media, Berlin (2011)

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