| | 1 | The past 40 years has seen enormous increases in man-made Radio Frequency (RF) radiation. However, the possible small and long term impacts of RF radiation are not well understood. This project seeks to discover if RF exposure impacts animal behaviors. In this experimental paradigm, animals are subject to RF exposure while their behaviors are video recorded. Deep Neural Networks (DNNs) are then tasked to correctly classify if the video contains exposure to RF or not. This uses DNNs as powerful pattern discovery tools, in contrast to their traditional uses of classification and generation. The project involves evaluating the accuracies of a number of DNN architectures on pre-recorded videos, as well as describe any behavioral patterns found by the DNNs. |
