Locust recognition and detection via aggregate channel features
conference contributionposted on 24.04.2019, 15:17 by Dewei Yi, Jinya Su, Wen-Hua Chen
Locust plagues are very harmful for food security, quality and quantity of agricultural products. With this consideration, precise locust detection is significant for preventing locust plagues. To achieve this task, aggregate channel feature (ACF) object detector with parameters optimization is applied to detect locusts. Experiment results show that ACF object detector with optimized parameters can achieve 0.39 for average precision and 0.86 for log-average miss rate. Moreover, ACF is a non-deep method using a simple model to detect objects. That is, the proposed method is promising to be embedded in a real-time locust detection system.
This work was supported by the U.K. Science and Technology Facilities Council under Grant ST/N006852/1, ST/N006712/1, and ST/N006836/1.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering