An IoT-enabled real-time overhead view person detection system based on Cascade-RCNN and transfer learning

Author:

Ahmad Misbah,Ahmed Imran,Jeon Gwanggil

Publisher

Springer Science and Business Media LLC

Subject

Information Systems

Reference53 articles.

1. Zou, Z., Shi, Z., Guo, Y., Ye, J.: Object detection in 20 years: a survey. arXiv preprint. arXiv: 1905.05055 (2019)

2. Yao, R., Lin, G., Xia, S., Zhao, J., Zhou, Y.: Video object segmentation and tracking: a survey. arXiv preprint. arXiv: 1904.09172 (2019)

3. Zhou, S., Ke, M., Qiu, J., Wang, J.: A survey of multi-object video tracking algorithms. In: Abawajy, J., Choo, K.K.R., Islam, R., Xu, Z., Atiquzzaman, M. (eds.) International conference on applications and techniques in cyber security and intelligence ATCI 2018, pp. 351–369. Springer, Cham (2019)

4. Ahmad, M., Ahmed, I., Khan, F.A., Qayum, F., Aljuaid, H.: Convolutional neural network-based person tracking using overhead views. Int. J. Distrib. Sens. Netw. 16(6), 1550147720934738 (2020)

5. Ahmed, I., Ahmad, M., Nawaz, M., Haseeb, K., Khan, S., Jeon, G.: Efficient topview person detector using point based transformation and lookup table. Comput. Commun. 147, 188 (2019)

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