Deep Learning in Aerial Systems Using Jetson

The adoption of unmanned aerial systems (UAS) has been steadily growing over the last decade. While UAS originated with military applications, they have proven to be beneficial in a variety of other fields including agriculture, geographical mapping, aerial photography, and search and rescue. These systems, however, require a person in the loop for remote control, scene recognition, and data acquisition. This increases the cost of operation and significantly limits the scope of applications to those where remote control is possible.Figure 1: Teams competing at AUVSI SUAS 2015. The ground targets can be seen in front of the teams. Courtesy of the AUVSI Seafarer Chapter. Through our work we aim to bring the power of deep learning to unmanned systems via two main thrusts. Optimization of deep neural networks for specific…

Link to Full Article: Deep Learning in Aerial Systems Using Jetson

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