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.

Abstract: Methods of evaluating animal activity relating to wildlife areas are disclosed that include running a digital classification routine to recognize particular species in a series of images. From those images data records are developed having the ability to identify timing information, the species, the location, celestial characteristics and atmospheric characteristics. The data records are analyzed to establish correlations between various associated features and the presence of the particular species. Data associated with future celestial characteristics and atmospheric characteristics is obtained and estimated probabilities of future appearances of the particular species are calculated and provided.