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Low-slow-small target recognition based on spatial vision network

机译:基于空间视觉网络的低速小目标识别

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Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.
机译:传统的光电监控是使用大量相同的摄像机监控的。为了确保监视区域的完全覆盖,此监视方法使用更多的摄像头,从而导致更多的监视和重复区域,以及更高的成本,从而导致更多的浪费。为了降低监测成本,解决发现,识别和跟踪低空,慢速,小目标的难题,提出了一种用于低速小目标识别的空间视觉网络。基于相机成像原理和监控模型,对空间视觉网络进行建模和优化。仿真实验结果表明,该方法具有良好的性能。

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