Abstract

This paper aims at the monitoring of birds and their ecological environment in the island and coastal wetland ecosystems. A new approach of island bird detection is proposed based on the Faster R-CNN (Regions with Convolutional Neural Networks) model under multiple backgrounds. It includes feature extraction, region proposal, bounding box regression, classification into the whole neural network structure. This key technology can automatically achieve automatic bird species identification and quantitative statistics in the faster computation speed. The details of constructing Faster R-CNN are described. In the end, many actual images are utilized to demonstrate the effectiveness of the proposed models.

摘要

本文旨在监测岛屿和沿海湿地生态系统中鸟类及其生态环境。提出了一种基于多种背景下的快速R-CNN（卷积神经网络区域）模型的海岛鸟类检测新方法。它包括特征提取，区域提议，边界框回归，分类为整个神经网络结构。该关键技术可以更快的计算速度自动实现鸟类自动识别和定量统计。描述了构建Faster R-CNN的细节。最后，利用许多实际图像来证明所提出模型的有效性。