The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A study on detecting drones using deep convolutional neural networks
Open accessAbstract
The object detection is a challenging problem in computer vision with various potential real-world applications. The objective of this study is to evaluate the deep learning based object detection techniques for detecting drones. In this paper, we have conducted experiments with different Convolutional Neural Network (CNN) based network architectures namely Zeiler and Fergus (ZF), Visual Geometry Group (VGG16) etc. Due to sparse data available for training, networks are trained with pre-trained models using transfer learning. The snapshot of trained models is saved at regular interval during training. The best models having high mean Average Precision (mAP) for each network architecture are used for evaluation on the test dataset. The experimental results show that VGG16 with Faster R-CNN perform better than other architectures on the training dataset. Visual analysis of the test dataset is also presented.
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Cited by
Machine Learning-Based Drone Detection and Classification: State-of-the-Art in Research
Taha, B., & Shoufan, A. (2019) · IEEE Access · doi:10.1109/access.2019.2942944 · Cited by 375
Survey on Anti-Drone Systems: Components, Designs, and Challenges
Park, S., Kim, H. T., Lee, S., Joo, H., & Kim, H. (2021) · IEEE Access · doi:10.1109/access.2021.3065926 · Cited by 325
Defending Airports from UAS: A Survey on Cyber-Attacks and Counter-Drone Sensing Technologies
Lykou, G., Moustakas, D., & Gritzalis, D. (2020) · Sensors · doi:10.3390/s20123537 · Cited by 268
Lygouras, E., Santavas, N., Taitzoglou, A., Tarchanidis, K., Mitropoulos, A., & Gasteratos, A. (2019) · Sensors · doi:10.3390/s19163542 · Cited by 253
Security and privacy issues of UAV: A survey
Zhi, Y., Fu, Z., Sun, X., & Yu, J. (2020) · Mobile Networks and Applications · doi:10.1007/s11036-018-1193-x · Cited by 226
Metadata
- Authors
- Saqib, M., Daud Khan, S., Sharma, N., & Blumenstein, M.
- Venue
- 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
- Publisher
- IEEE
- Published
- 2017-08
- Pages
- 1-5
- OpenAlex
- W2765322173
- Cited by
- 177
- References
- 6
- FWCI
- 4.77
- Type
- conference paper
- Language
- en
- Open access
- green
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