Deep Learning Applications for Fauna and Flora Recognition

Dear Colleagues,

Species identification is one of the most important topics in the field of image and video analysis. Both in air and underwater, and for fauna and flora, species identification and measurement is an essential tool to estimate biomass or population distributions. Evident changes within ecosystems can be used to inform important management decisions, especially for vulnerable species. The automation of species identification has been under development for many years, based on computer vision and image processing techniques, achieving good identification success rates. More recently, deep learning has produced even higher levels of success for species identification, in the region of 95% accuracy in the best cases.

The main objective of this Special Issue is to demonstrate the effectiveness of deep learning applied to species identification across a range of fauna, flora and environments. A secondary aim is to evaluate the use of different sensors, specifically imaging and video systems using different spectral sensitivities, such as thermal infrared imagers.

Prof. Dr. Mark Shortis
Guest Editor

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