wish to make some changes: different output & no pre-determined images features

[lvapeab]

wish to make some changes: different output & no pre-determined images features

[lvapeab]

Hi @ron-weiner ,

thanks for your interest in the project.

You definitely can use it for your problem. Instead a sequence predictor, you need a (binary) classifier. Therefore, you can remove the decoder RNN and substitute it by a classifier (e.g. Dense layers). We have some projects that use this approach. Please, take a look at:

• sentence-selectioNN: This project classifies text into "in-domain" or "out-of-domain" (as yours, a binary classification problem). It computes a representation of the text using RNNs or CNNs and applies Dense layers afterwards.

• VIBIKNet: This tackles the visual question answering problem. It encodes an image and a question, merges them and predicts the answer as a classification problem.

Cheers!

PS: Those repositories may contain deprecated code w.r.t. the current version of Keras, but I think you can take the main flavour of the changes required for your problem ;)

[ron-weiner]

Thanks for the quick reply!
I want to rewrite it for python 3, it will we more handy for the future.
Can you focus me on what i should dismiss if i don't want to use any features on the frames?

Do you think that this project is the up to date in that field? do you have/know additional projects in that level which might be good to start with?

Thank you!!

Cheers