基于二值语义分割网络的遥感建筑物检测

来源 :光学学报 | 被引量 : 0次 | 上传用户：liongliong469

【摘要】

：

针对遥感建筑物实时检测中深度卷积网络资源消耗大和硬件移植难的问题,提出一种基于二值与浮点数混用方法的语义分割网络MBU-Net。通过对FU-Net网络全局权重进行二值化处理来压缩模型大小,并将占少量参数的网络输出层权重替换成浮点型(MBU-Net),解决了全局二值网络(GBU-Net)检测精度差、训练缓慢的问题。在QuickBird卫星遥感数据集上进行实验,MBU-Net的像素准确率为82.33%

【作者】

：

朱天佑董峰龚惠兴

【机构】

：

中国科学院红外探测与成像技术重点实验室,上海200083中国科学院上海技术物理研究所,上海200083中国科学院大学,北京100049

【出处】

：

光学学报

【发表日期】

：

2019年12期

【关键词】

：

遥感卫星图像建筑物检测语义分割二值神经网络 remote sensing satellite images building detection sem

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基于二值语义分割网络的遥感建筑物检测

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