Image data set based on the age of giant pandas

The conservation of the giant panda (Ailuropoda melanoleuca), as an iconic
vulnerable species, has received great attention in the past few decades.
As an important part of the giant panda population survey, the age
distribution of giant pandas can not only provide useful instruction but
also verify the effectiveness of conservation measures. The current
methods for determining the age groups of giant pandas are mainly based on
the size and length of giant panda feces and the bite value of intact
bamboo in the feces, or in the case of a skeleton, through the wear of
molars and the growth line of teeth. These methods have certain flaws that
limit their applications. In this study, we developed a deep learning
method to study age group classification based on facial images of captive
giant pandas and achieved an accuracy of 85.99% on EfficientNet. The
experimental results show that the faces of giant pandas contain some age
information which is mainly concentrated between the eyes of giant pandas.
In addition, the results also indicate that it is feasible to identify the
age groups of giant pandas through the analysis of facial images.