Multi-object tracking based on deep associated features for UAV applications

Multi-object tracking(MOT) techniques have been increasingly applied in a diverse range of tasks. Unmanned aerial vehicle(UAV) is one of its typical application scenarios. Due to the scene complexity and the low resolution of moving targets in UAV applications, it is difficult to extract target features and identify them. In order to solve this problem, we propose a new re-identification(re-ID) network to extract association features for tracking in the association stage. Moreover, in order to reduce the complexity of detection model, we perform the lightweight optimization for it. Experimental results show that the proposed re-ID network can effectively reduce the number of identity switches, and surpass current state-of-the-art algorithms. In the meantime, the optimized detector can increase the speed by 27% owing to its lightweight design, which enables it to further meet the requirements of UAV tracking tasks.

Low-Light Enhancer for UAV Night Tracking Based on Zero-DCE++

Unmanned aerial vehicle (UAV) target tracking tasks can currently be successfully completed in daytime situations with enough lighting, but they are unable to do so in nighttime scenes with inadequate lighting, poor contrast, and low signal-to-noise ratio. This letter presents an enhanced low-light enhancer for UAV nighttime tracking based on Zero-DCE++ due to its ad-vantages of low processing cost and quick inference. We developed a light-weight UCBAM capable of integrating channel information and spatial features and offered a fully considered curve projection model in light of the low signal-to-noise ratio of night scenes. This method significantly improved the tracking performance of the UAV tracker in night situations when tested on the public UAVDark135 and compared to other cutting-edge low-light enhancers. By applying our work to different trackers, this search shows how broadly applicable it is.

Recent development of unmanned aerial vehicle for plant protection in East Asia

Recently,the growing use of unmanned aerial vehicles(UAV)for pesticide application has been reported against a wide range of crops with promising results in East Asian countries such as Japan,South Korea and China.This UAV-based application technology for agrochemicals is considered as a high efficiency alternative to the conventional manual spray operations and a low-cost choice as compared to the classical manned aerial application.However,the technology adoption rate and the designed optimal sprayer suitable for drone application for small scale farm remains at the development stage in China and also in Japan.This paper reports the current status of drone pesticide application in China and makes comparisons with its neighbor countries Japan and South Korea in terms of different UAV platforms and their implementation in plant protection for different crops.Challenges and opportunities for future development of UAV-based pesticide application technology are also discussed.