A survey and performance evaluation of deep learning methods for small object detection

Author:

Liu Yang,Sun Peng,Wergeles Nickolas,Shang Yi

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference111 articles.

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2. Bell, S., Lawrence Zitnick, C., Bala, K., & Girshick, R. (2016). Inside-Outside Net: Detecting objects in context with skip pooling and recurrent neural networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR; pp. 2874-2883). Las Vegas: IEEE Xplore. Retrieved from https://openaccess.thecvf.com/content_cvpr_2016/html/Bell_Inside-Outside_Net_Detecting_CVPR_2016_paper.html.

3. Soft-NMS – improving object detection with one line of code;Bodla,2017

4. Cai, Z., Fan, Q., Feris, R. S., & Vasconcelos, N. (2016). A unified multi-scale deep convolutional neural network for fast object detection. European Conference on Computer Vision. 9908, pp. 354–370. Cham: Springer. tps://doi.org/10.1007/978-3-319-46493-0_22.

5. Cao, G., Xie, X., Yang, W., Liao, Q., Shi, G., & Wu, J. (2018). Feature-fused SSD: fast detection for small objects. Ninth International Conference on Graphic and Image Processing (ICGIP 2017). 10615, p. 106151E. Qingdao, China: Proc. SPIE. https://doi.org/10.1117/12.2304811.

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