基于deeplabv3plus网络实现了虹膜图像分割以及水果图像分割
deeplabv3+包含三部分backbone、ASPP以及Decoder三部分。backbone获取一个低层次特征和一个高层次特征,然后将高层次特征输入到ASPP得到多尺度特征,再对多尺度特征上采样与低层次特征融合得到包含语义特征和细粒度特征的融合特征,最后对融合特征上采样,得到mask。
感谢王博士提供的虹膜图像分割数据IrisParseNet
基于deeplabv3plus网络实现了虹膜图像分割以及水果图像分割
基于deeplabv3plus网络实现了虹膜图像分割以及水果图像分割
deeplabv3+包含三部分backbone、ASPP以及Decoder三部分。backbone获取一个低层次特征和一个高层次特征,然后将高层次特征输入到ASPP得到多尺度特征,再对多尺度特征上采样与低层次特征融合得到包含语义特征和细粒度特征的融合特征,最后对融合特征上采样,得到mask。
感谢王博士提供的虹膜图像分割数据IrisParseNet
A great job,could you please send me a link of complete "CASIA-distance" dataset? thank you!
Hi! Thanks for your job. I saw you add dropout in both ASPP and the decoder. However, I could't find any sign of using dropout in the original paper. Is this a mistake?
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