Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys

Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys

Unoccupied aerial systems (UASs) may provide cheaper, safer, and more accurate and precise alternatives to traditional waterfowl survey techniques while also reducing disturbance to waterfowl. We evaluated availability and perception bias based on machine-learning-based non-breeding waterfowl count...

Full description

Bibliographic Details
Main Authors: Reid Viegut, Elisabeth Webb, Andrew Raedeke, Zhicheng Tang, Yang Zhang, Zhenduo Zhai, Zhiguang Liu, Shiqi Wang, Jiuyi Zheng, Yi Shang
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Drones
Subjects:
waterfowl
wetland
abundance estimation
drones
artificial intelligence
detection probability
Online Access:https://www.mdpi.com/2504-446X/8/2/54

Similar Items

Similar Items