Vehicle Detection Based on Semantic Segmentation

Polat, Aslı Nur; Oral, Emin Argun; KUMBASAR, NİDA; Özbek, İbrahim Yücel; ABDO, Hussein Mahmood

doi:10.1145/3297156.3297269

Bildiri Tam Metin Bildiri Uluslararası 2018

Vehicle Detection Based on Semantic Segmentation

Aslı Nur Polat, Emin Argun Oral, NİDA KUMBASAR, İbrahim Yücel Özbek, Hussein Mahmood ABDO

ISASE2018 26.11.2018–28.11.2018 · 26.11.2018

DOI ile aç

Özet

Combined with semantic segmentation and visual attention mechanism, a new method for UAV detection in complex background is presented. The semantic segmentation of target image, which is implemented by Mask R-CNN, is used to exclude invalid regions. Then the processes of small target detection based on visual attention mechanism is built. This method is used to detecting the position of UAV in the sky. The effectiveness of algorithm proposed in this paper is proved by a large number of experiments.

Anahtar kelimeler

Semantic segmentation Mask R-CNN visual attention mechanism UAV detection

Atıf için künye

Polat, A. N., Oral, E. A., KUMBASAR, N., Özbek, İ. Y., & ABDO, H. M. (2018). Vehicle Detection Based on Semantic Segmentation. ISASE2018. https://doi.org/10.1145/3297156.3297269

BibTeX

@inproceedings{polat2018-181090,
  author = {Polat, Aslı Nur and Oral, Emin Argun and KUMBASAR, NİDA and Özbek, İbrahim Yücel and ABDO, Hussein Mahmood},
  title = {Vehicle Detection Based on Semantic Segmentation},
  booktitle = {ISASE2018},
  year = {2018},
  doi = {10.1145/3297156.3297269},
  url = {https://akademik.atauni.edu.tr/yayinlar/181090-vehicle-detection-based-on-semantic-segmentation}
}