Comments (3)
While the calculation is the same, the two modules have different functionality. The predictors are tasked with predicting the target masks/edges directly, while the queries are used for the attention merging mechanism to merge the predictors' outputs into a single, final prediction.
I recommend reading section III C) in the paper: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9383809. Let me know if that clears your question or you have additional questions.
from hed-unet.
Thank you for taking the time to answer my question.I think my question has been completely answered.
I tried to use the resolution attention mechanism in your article to solve the problems in my research, and achieved good results.
Finally, thank you again for your meticulous and warm help.
from hed-unet.
Glad to hear that! Feel free to reopen the issue if you have any more questions!
from hed-unet.
Related Issues (18)
- How could I get the complete images on result HOT 1
- Training steps HOT 4
- Is the image input during the training process the original image and the binary image? HOT 17
- Testing data HOT 7
- Whether this program can handle .png files. If you canβt handle it, can you convert the .tif file to a .png file? HOT 1
- AttributeError: 'Array' object has no attribute 'numpy' HOT 1
- RuntimeError: Given groups=1, weight of size [16, 3, 1, 1], expected input[8, 4, 256, 256] to have 3 channels, but got 4 channels instead HOT 10
- Hello, my training is successful, then I would like to ask how to test my own data? HOT 1
- About training HOT 21
- About Loss HOT 5
- About mutil classes HOT 19
- Hed HOT 7
- Weight Map HOT 2
- I have some questions about testing. HOT 6
- Does the edge detection task have an impact on the semantic segmentation task in this model? HOT 1
- Can you please share the pre-trained weights for interence HOT 1
- Can the author provide code for prediction
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