Multi-Background Island Bird Detection Based on Faster R-CNN

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.