计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 253-257.doi: 10.11896/jsjkx.191100006
刘俊琦1, 李智2, 张学阳2
LIU Jun-qi1, LI Zhi2, ZHANG Xue-yang2
摘要： 为剔除船只候选区域中的虚警目标,提出了一种基于信息熵和残差神经网络的多层次虚警鉴别方法。首先,基于船只和虚警图像切片在信息熵上的差异,采用信息熵阈值来去除候选区域中的大部分虚警。为进一步确认船只目标,设计了一种用于图像切片分类的深层残差神经网络模型,并采用网络“微调”的迁移学习策略对图像分类网络模型进行训练,实现对船只目标和虚警的自动分类。实验结果表明,该方法取得了不错的鉴别效果,能有效剔除岛屿、云层、海杂波等虚警,方法简单高效,后续无须进行复杂的鉴别工作。
中图分类号:
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