In practice, it is hard to accurately estimate the population size of giant pandas because of their small and sparsely distributed population in large habitats with complex forests and mountains. Also, they reflect the vulnerability of ecosystems in the area of study. The giant panda population and its dynamics are not only the basis for delineating nature reserves, establishing local conservation management institutions, and establishing ecological corridor zones but also the important indicators for evaluating the effectiveness of conservation management schemes. Ecologists have been trying to identify individual animals, including giant panda ( Ailuropoda melanoleuca) to accurately estimate their population and to study their spatial behavior. (Xiangjiang et al., 2009) This information is vital for developing suitable animal protection strategies (Pollard, Blumstein, & Griffin, 2010 Zheng et al., 2016). (Miller, Joyce, & Waits, 2005 Smallwood & Schonewald, 1998 Solberg, Bellemain, Drageset, Taberlet, & Swenson, 2006 Zhan et al., 2006). Accurate estimation of their population sizes is crucial for developing effective conservation and management schemes. Population size is an important factor determining whether species can persist in nature and also an important indicator of regional biodiversity (McNeely, Miller, Reid, Mittermeier, & Werner, 1990). This noninvasive approach is much more cost-effective than the approaches used in the previous panda surveys.
It enables the use of the cameras installed in their habitat for monitoring their population and behavior.
In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition.The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image-based panda face recognition method. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas.
As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades.
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