计算机科学 ›› 2021, Vol. 48 ›› Issue (7): 190-198.doi: 10.11896/jsjkx.200800225
陈志文1, 王坤1, 周广蕴2, 王旭2, 张晓丹2, 朱虎明1
CHEN Zhi-wen1, WANG Kun1, ZHOU Guang-yun2, WANG Xu2, ZHANG Xiao-dan2, ZHU Hu-ming1
摘要: 基于深度神经网络的SAR图像变化检测算法由于精确率高等优点,已被广泛应用在农业检测、城市规划以及森林预警等多个领域。设计了基于胶囊网络的SAR图像变化检测算法,针对其模型复杂度高、参数量大等问题,提出了基于权重剪枝的模型压缩方法。该方法对其胶囊网络参数进行逐层分析,针对不同类型的层采取不同的剪枝策略,对网络中冗余的参数进行剪枝,随后对剪枝后的网络进行微调,从而提高了剪枝后模型的检测性能。最后,通过对模型中保留下来的参数进行压缩存储,显著降低了模型所占用的存储空间。在4组真实SAR图像上的实验结果证明了所提出的模型压缩方法的有效性。
中图分类号:
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