An instance segmentation framework based on parallelogram mask for crop row detection in various farmlands
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17443-x.pdf
Reference23 articles.
1. Vidović I, Cupec R, Željko H (2016) Crop row detection by global energy minimization. Pattern Recognit 55:68–86. https://doi.org/10.1016/j.patcog.2016.01.013
2. English A, Ross P, Ball D, Corke P (2014) Vision based guidance for robot navigation in agriculture. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp 1693–1698. https://doi.org/10.1109/ICRA.2014.6907079
3. English A, Ross P, Ball D, Upcroft B, Corke P (2015) Learning crop models for vision-based guidance of agricultural robots. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp 1158–1163. https://doi.org/10.1109/IROS.2015.7353516
4. Neven D, Brabandere BD, Georgoulis S, Proesmans M, Gool LV (2018) Towards end-to-end lane detection: an instance segmentation approach. In: 2018 IEEE Intelligent Vehicles symposium (IV), pp 286–291. https://doi.org/10.1109/IVS.2018.8500547
5. Adhikari SP, Yang H, Kim H (2019) Learning semantic graphics using convolutional encoder-decoder network for autonomous weeding in paddy. Frontiers in Plant Science 10. https://doi.org/10.3389/fpls.2019.01404
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