Chimney and condensing tower detection based on faster R-CNN in high resolution remote sensing images
Yuan Yao, Zhiguo Jiang, Haopeng Zhang, Bowen Cai, Gang Meng, Deshan Zuo · 2017
The persistent haze weather in North China has aroused extensive attention to environmental protection. Among all pollution resources, the anthropogenic emission by fossil fuel power plants plays an important role. To assist the environmental protection administration monitoring fossil fuel power plants, we propose an effective approach in this paper to learn an integrated model for chimney and condensing tower detection based on Faster R-CNN in high resolution remote sensing images. Our method can detect chimneys and condensing towers under different imaging condition efficiently and accurately. Experimental results on a self-collected dataset demonstrate the effectiveness of the proposed method.