You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi all,
I am working with a feature extractor (Inception V3, VGG16, whatever) plus an LSTM for sequences classification (let's say 3 sec. each one). There's any way to use GradCam in order to obtain areas activation on the input sequences? Right now, I just classify one sequence without single frame classification, is still possible apply GradCam to this network?
I didn't find any example code about it, but just for GradCam applied to single feature extractor.
Thanks in advance for the help,
Gabriele
The text was updated successfully, but these errors were encountered:
Hi,
I used the standard way by applying grad-cam to each frame within the sequence. Since the CNN+LSTM network internally predict the class for each frame, you can then apply grad-cam to them. In my case this represents the area within every image in which the network focused at prediction time.
I applied the implementation of grad-cam tensorflow 2: https://github.com/ismailuddin/gradcam-tensorflow-2
Hi all,
I am working with a feature extractor (Inception V3, VGG16, whatever) plus an LSTM for sequences classification (let's say 3 sec. each one). There's any way to use GradCam in order to obtain areas activation on the input sequences? Right now, I just classify one sequence without single frame classification, is still possible apply GradCam to this network?
I didn't find any example code about it, but just for GradCam applied to single feature extractor.
Thanks in advance for the help,
Gabriele
The text was updated successfully, but these errors were encountered: