Comments (4)
sunyinhui
commented on May 13, 2024
I can get the message. please help me
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kevinlin311tw
commented on May 13, 2024
Hi @sunyinhui
Sorry. Since this project is a work in progress, some parameter names may confuse. We will improve this as soon as possible.
The red and green parts represent two different objective functions. They are not layers, so they don't have "nodes".
The green one represents the K1_EuclideanLoss, and the red one is K2_EuclideanLoss.
K1_EuclideanLoss will enforce each node in encode_neuron to be 0 or 1.
K2_EuclideanLoss will ensure each node in encode_neuron has a 50% chance of being 0 or 1.
Btw, our binary codes are learn in the encode_neuron. During testing, we extract the binary codes from encode_neuron
Should you have any question about the paper, please feel free to email me.
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sunyinhui
commented on May 13, 2024
Oh , Thanks! ^_^
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sunyinhui
commented on May 13, 2024
Hi Kevinlin，I can not underdtand deeply the loss_beta and loss_gamma . Please help me. Thanks
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Related Issues (20)
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- Hello，how do you dispose multi_label dataset?,like UT-ZAP50K and NUS-WIDE? Can you tell me in detail?
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