ENVIRONMENTAL MONITORING USING DRONE IMAGES AND CONVOLUTIONAL NEURAL NETWORKS - Thomazella, R. [UNESP]; Castanho, J. E. [UNESP]; Dotto, F. R. L. [UNESP]; Rodrigues Junior, O. P.; Rosa, G. H. [UNESP]; Marana, A. N. [UNESP]; Papa, J. P. [UNESP]; IEEE (Ieee, 2018)
Recently, drone images have been used in a number of applications, mainly for pollution control and surveillance purposes. In this paper, we introduce the well-known Convolutional Neural Networks in the context of environmental monitoring using drone images, and we show their robustness in real-world images obtained from uncontrolled scenarios. We consider a transfer learning-based approach and compare two neural models, i.e., VGG16 and VGG19, to distinguish four classes: water, deforesting area, forest, and buildings. The results are analyzed by experts in the field and considered pretty much reasonable.
Keywords: Land-use classification; Drones; Convolutional Neural Networks