Optimized Small Waterbird Detection Method Using Surveillance Videos Based on YOLOv7.

ABSTRACT: Waterbird monitoring is the foundation of conservation and management strategies in almost all types of wetland ecosystems. China's improved wetland protection infrastructure, which includes remote devices for the collection of larger quantities of acoustic and visual data on wildlife species, increased the need for data filtration and analysis techniques. Object detection based on deep learning has emerged as a basic solution for big data analysis that has been tested in several application fields. However, these deep learning techniques have not yet been tested for small waterbird detection from real-time surveillance videos, which can address the challenge of waterbird monitoring in real time. We propose an improved detection method by adding an extra prediction head, SimAM attention mo

SUBMITTER: Lei J 

PROVIDER: S-EPMC10295383 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature