Ilya Kibardin
Student at Moscow Institute of Physics and Technology
Kaggle Master.
Arthur Fattakhov
Student at Moscow Institute of Physics and Technology
Kaggle Master.
Arthur Kuzin
Head of Computer Vision at X5 Retail Group.
Kaggle Grandmaster.
Ruslan Dautov
Graduate student at Shenzhen University
Vladimir Iglovikov
Computer Vision Engineer at Lyft, Level5
Kaggle Grandmaster
We want State Of The Art approach => Deep Learning
Deep Learning benefits from large amounts of train data => get more data
We need unmanipulated data => filtering
Filtered on:
Final train and validation sets
Raw data 500Gb
We want the model to be robust to:
=> Apply augmentations on the fly
We used:
In green, parameters range used during training.
In green, parameters range used during training.
In green, parameters range used during training.
In green, parameters range used during training.
An extended version of the presentation:
Google => Forensic Deep Learning: Kaggle Camera Model Identification Challenge