Automatic Identification of Stone-Handling Behaviour in Japanese
  Macaques Using LabGym Artificial Intelligence
Théo Ardoin Cédric Sueur
The latest advancements in artificial intelligence technology have opened
doors to the analysis of intricate behaviours. In light of this, ethologists
are actively exploring the potential of these innovations to streamline the
time-intensive process of behavioural analysis using video data. In the realm
of primatology, several tools have been developed for this purpose.
Nonetheless, each of these tools grapples with technical constraints that we
aim to surmount. To address these limitations, we have established a
comprehensive protocol designed to harness the capabilities of a cutting-edge
tool, LabGym. Our primary objective was to evaluate LabGym's suitability for
the analysis of primate behaviour, with a focus on Japanese macaques as our
model subjects. We have successfully developed a model that demonstrates a high
degree of accuracy in detecting Japanese macaques stone-handling behaviour. Our
behavioural analysis model was completed as per our initial expectations and
LabGym succeed to recognise stone-handling behaviour on videos. However, it is
important to note that our study's ability to draw definitive conclusions
regarding the quality of the behavioural analysis is hampered by the absence of
quantitative data within the specified timeframe. Nevertheless, our model
represents the pioneering endeavour, as far as our knowledge extends, in
leveraging LabGym for the analysis of primate behaviours. It lays the
groundwork for potential future research in this promising field.