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Automatic target recognition on land using three dimensional (3D) laser radar and artificial neural networks

机译:使用三维(3D)激光雷达和人工神经网络的自动目标识别

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During combat, measuring the dimensions of targets is extremely important for knowing when to fire on the enemy. The importance of identifying a known target on land emphasizes the importance of techniques devoted to automatic target recognition. Although a number of object-recognition techniques have been developed in the past, none of them have provided the desired specifics for unidentified target recognition. Studies on target recognition are largely based on images that assume that images of a known target can be readily viewed under any circumstance. But this is not true for military operations conducted on various terrains under specific circumstances. Usually it is not possible to capture images of unidentified objects because of weather, inadequate equipment, or concealment. In this study, a new approach that integrates neural networks and laser radar has been developed for automatic target recognition in order to reduce the above-mentioned problems. Unlike current studies, the proposed model uses the geometric dimensions of unidentified targets in order to detect and recognise them under severe weather conditions.
机译:在战斗中,测量目标的尺寸对于知道何时向敌人开火极为重要。确定陆地上已知目标的重要性强调了致力于自动目标识别的技术的重要性。尽管过去已经开发了许多对象识别技术,但是它们都没有为未识别的目标识别提供所需的细节。关于目标识别的研究主要基于图像,这些图像假定在任何情况下都可以轻松查看已知目标的图像。但这不适用于在特定情况下在各种地形上进行的军事行动。通常,由于天气,设备不足或隐藏,无法捕获未识别物体的图像。在这项研究中,为了减少上述问题,已经开发了一种将神经网络和激光雷达相集成的新方法来进行自动目标识别。与当前的研究不同,该模型使用未识别目标的几何尺寸来检测和识别恶劣天气条件下的目标。

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