Blog

Learn About Our Meetup

5000+ Members

MEETUPS

LEARN, CONNECT, SHARE

Join our meetup, learn, connect, share, and get to know your Toronto AI community. 

JOB POSTINGS

INDEED POSTINGS

Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.

CONTACT

CONNECT WITH US

Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.

[D] Transfer-Learning / Finetuning pretrained Imagenet CNNs for a resolution higher than 244×244- Any advice?

Does anyone have experience with finetuning a resnet / VGG model pretrained on imagenet but using a higher resolution for the inputs?

Any advice, papers or slides are most welcome!

Background:

I am currently working on binary classification of images and have had pretty good success by finetuning a resnet50 pretrained on imagenet (this is a pretty good guide https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html ). I have only a few hundred images of each class, so overfitting is a massive concern and thus unfreezing the lower parts of the resnet would not work.

However, my images are much higher resolution than imagenet – most tutorials I have found seem to rescale images to 244×244 which is what I am doing right now, but I think that downscaling the images a bit less might make the task easier to solve.

Keras resnet50 implementation accepts higher resolution images, but the model doesn’t improve during training at all.

submitted by /u/AuspiciousApple
[link] [comments]

Next Meetup

 

Days
:
Hours
:
Minutes
:
Seconds

 

Plug yourself into AI and don't miss a beat

 


Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.