An Object Detection Algorithm for UAV Reconnaissance Image Based on Deep Convolution Network

In recent years, the UAV technology has developed rapidly and played an important role in many fields, especially in intelligence, reconnaissance, and monitoring. Object detection can provide accurate target location and target category for reconnaissance missions, providing detailed command information for commanders. However, the current object detection algorithm based on deep convolution network does not work well on detection for small objects and so cannot be applied to small objects in the reconnaissance image of UAV. In this paper, an object detection algorithm for UAV reconnaissance image based on deep convolution network is proposed. The image is adaptively divided according to the UAV flight parameters and the payload parameters before sent into the network. Through this way, small objects can be located and classified in a high accuracy of location and classification. This method can detect objects with small size, multiple quantities, and multiple categories on UAV.