An Intelligent Human Activity Recognizer for Visually Impaired People Using VGG-SVM Model-Reference-Cited by-同舟云学术

An Intelligent Human Activity Recognizer for Visually Impaired People Using VGG-SVM Model

Published:2022 Issue: Volume: Page:356-368
ISSN:0302-9743
Container-title:Advances in Computational Intelligence
language:
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Author:

Saleem Rabeeya,Ahmad Tauqir,Aslam Muhammad,Martinez-Enriquez A. M.

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-19496-2_28

Reference31 articles.

1. Fast facts of common eye disorders, June 2020. https://www.cdc.gov/visionhealth/basics/ced/fastfacts.htm

2. Vision impairment and blindness (2022). https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment

3. Aparna, R., Chitralekha, C., Chaudhari, S.: Comparative study of CNN, VGG16 with LSTM and VGG16 with bidirectional LSTM using kitchen activity dataset. In: 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), pp. 836–843. IEEE (2021)

4. Cao, Z., Simon, T., Wei, S.E., Sheikh, Y.: Realtime multi-person 2D pose estimation using part affinity fields. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7291–7299 (2017)

5. Dai, C., Liu, X., Lai, J.: Human action recognition using two-stream attention based LSTM networks. Appl. Soft Comput. 86, 105820 (2020)

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