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The core code of AGCA: An Adaptive Graph Channel Attention Module for Steel Surface Defect Detection

License: MIT License

Python 100.00%
pytorch surface-detection attention-model deep-learning

agca's Issues

A0 needs to be placed on the GPU GPU和CPU

作者您好,通过这步操作将A0放在GPU上,
image
但是其他模型和数据都还在cpu上
image
因此,在执行这步操作的时候:
image
就报错一个数据在GPU、一个数据在CPU,无法进行运算,这个问题应该如何解决呢

关于模型参数问题

image
作者您好,看论文的时候关于这部分的参数量我有些疑问,为什么加ECA反而参数量还降低了呢?而且加上其他CBAM参数量为啥保持不变呀?

网络代码

作者,您好,可以分享完整的网络代码吗

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