sidhant_Naveria:

by scale the activation you mean, just multiply a scalar value to the output of left branch and then concatenate it with the right branch.


Yes, I understood that would be your use case given “provide weights before concatenation”.
If that’s not the case, please provide more information about the method you would like to use.



 sidhant_Naveria:

No i haven’t about anything which states left image will the more features, it just i come up to the conclusion after training left image and right image separately


I was asking about the general assumption that scaling a feature (or however your weighting should look like) corresponds to a higher “feature importance”.