Abstract: Methods of evaluating deer are disclosed including examples predicting the activity of deer using artificial intelligence object detection. Gender evaluations and subsequent gender reevaluations based on contextual information are described for better understanding of the population composition. Correlation factors are taught for predictive analysis used to evaluate conditions in which deer are likely to reappear and deer characteristics are presented in methods of evaluating the repeat appearances of deer. A variety of group matching techniques are taught for use in developing more accurate accounting of the true number of unique deer sighted.

Abstract: Methods of evaluating populations of deer are disclosed that include receiving a series of images containing deer; utilizing artificial intelligence object detection to identify deer from the series of images; utilizing spatial relationships between points to create an image scale; identifying a set of metrics associated with the deer; evaluating the gender of the deer; and utilizing a repeat matching technique to evaluate if the deer is a likely reappearance of a previously identified deer.