Improving Thermal Object Detection for Optimized Deep Neural Networks on Embedded Devices-Reference-Cited by-同舟云学术

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Improving Thermal Object Detection for Optimized Deep Neural Networks on Embedded Devices

Published:2023 Issue: Volume: Page:83-94
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Mebtouche Naoual El-Djouher,Baha Nadia,Kaddouri Nassim,Zaghdar Abderrahim,Redjil Abou Bakr Essadiq

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-4484-2_7

Reference22 articles.

1. Takumi, K., Watanabe, K., Ha, Q., et al.: Multispectral object detection for autonomous vehicles. In: Proceedings of the Thematic Workshops of ACM Multimedia, Mountain View, CA, USA (2017)

2. Wang, Y., Chen, Y., Choi, J, C, C., Kuo, J.: towards visible and thermal drone monitoring with convolutional neural networks. APSIPA Trans. Signal Inf. Process. 8, E5 (2019)

3. Mebtouche, N.ED., Baha, N.: Robust UAV detection based on saliency cues and magnified features on thermal images. Multimedia Tools Appl. (2022)

4. Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich Feature hierarchies for accurate object detection and semantic segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 580–587 (2014)

5. Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779–788 (2016)

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