Studying the social interactions among animals is essential to understanding their behavior and the consequences it has for ecology and neurology. The Social Behavior Atlas (SBeA), developed by researchers at the Brain Cognition and Brain Disease Institute (BCBDI) of the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences, is a novel technique that tracks and analyzes the behavior of numerous animals in three dimensions (3D) using artificial intelligence (AI).
This work, which was published in Nature Machine Intelligence, offers a novel method for analyzing the behavior of multiple animals at once. In contrast to conventional approaches, which necessitate pre-established social behavior categories, the SBeA framework makes use of an AI few-shot learning algorithm. This algorithm is capable of identifying similar-looking animals with over 90% accuracy, which opens the door to the identification of hitherto unknown variances in animal social behavior.
The SBeA framework’s capacity to synthesis vast volumes of data and train models with increased accuracy is one of its main advantages. The study’s corresponding author, Wei Pengfei, claims that this leads to a more accurate estimate of 3D social gestures.
Identifying individual animals, calculating 3D social position, and examining nuanced social interactions in a variety of species, including domestic dogs, birds, and mice, are all made possible by the SBeA technology. Moreover, its potential for cross-species applications creates new opportunities for researching animal social behavior.
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