Automatic ship detections in complex background during the day and night in infrared images is an important task. Additionally, we want to have the capability to detect the ships in various scales, orientations, and shapes. In this paper, we propose the use of neural network technology for this purpose. The algorithm used for this task is the Deep Neural Machine (DNM), which contains three different parts (backbone, neck, and head). Combining all three steps, this algorithm can extract the features, create prediction layers using different scales of the backbone, and give object predictions at different scales. The experimental results show that our algorithm is robust and efficient in detecting ships in complex background.
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