在这个示例中,我们首先定义了HED的网络结构,然后定义了U-Net的网络结构,最后将两者连接在一起构成HED-UNet模型。通过使用Keras库的Model类,我们可以建立一个端到端的神经网络模型。 当我们为HED-UNet模型传入输入图像后,模型将输出一个与输入图像大小相同的特征图,其中包含图像的边缘信息。 总结 HED-UNet是一种用于...
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This framework is trained to detect the coastline in Sentinel-1 images of the Antarctic coastline. Its performance is then compared to conventional single-task approaches, and shown to outperform these methods. The code is available at https://github.com/khdlr/HED-UNet 展开 ...
Code for HED-UNet, a model for simultaneous semantic segmentation and edge detection. Glacier Fronts This model was originally developed to detect calving front margins in Antarctica from Sentinel-1 SAR imagery. As the original dataset isn't publicly available, this repository contains an adaption of...
Since the southern and coastal land is white iceberg, it is more difficult to distinguish the sea surface from the land. In the experiment, many existing deep learning models cannot accurately predict the Antarctic coast, but HED-Unet introduces the idea that humans will perform segmentation and ...
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By using different optimizers and loss functions in the HED-Unet model, the experiment verifies that Adam + Focal loss has the best performance. The results also show that the deep learning model, HED-Unet, can effectively improve the accuracy of the sea–land segmentation to 97% in a ...
By using different optimizers and loss functions in the HED-Unet model, the experiment verifies that Adam + Focal loss has the best performance. The results also show that the deep learning model, HED-Unet, can effectively improve the accuracy of the sea–land segmentation to 97% in a ...