The prevalent deep learning approach achieve a great success in many detection task. However, due to the limited features and complicated background, it is still a challenge to apply it to small target detection in infrared image. In this paper, a novel method based on convolutional neural network is proposed to solve the small target detection problem. Firstly, the image feed to neural network is preprocessed in order to enhance the target characteristic by encompassing space and time information. Then the spatial-temporal datum is used to train a custom designed lightweight network dedicated to small target detection. At last, the well trained model is used for inference of infrared video. Furthermore, several tricks are also employed to improve the efficiency of the network so that it is able to operate in real time .The experimental result demonstrate the presented method have achieved decent performance on small target detection task.
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