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Image Segmentation: Tips and Tricks from 39 Kaggle Competitions

Image Segmentation: Tips and Tricks from 39 Kaggle Competitions

Jakub Czakon's photo
Jakub Czakon
·May 19, 2020

Imagine if you could get all the tips and tricks you need to hammer a Kaggle competition. I have gone over 39 Kaggle competitions including

Contents

  • External Data
  • Preprocessing
  • Data Augmentations
  • Modeling
  • Hardware Setups
  • Loss Functions
  • Training Tips
  • Evaluation and Cross-validation
  • Ensembling Methods
  • Post Processing

External Data

Data Exploration and Gaining insights

Preprocessing

Data Augmentations

Modeling

Architectures

Hardware Setups

Loss Functions

Training tips

Evaluation and cross-validation

Ensembling methods

Post Processing

Final Thoughts

Hopefully, this article gave you some background into image segmentation tips and tricks and given you some tools and frameworks that you can use to start competing.

We’ve covered tips on:

  • architectures
  • training tricks,
  • losses,
  • pre-processing,
  • post processing
  • ensembling
  • tools and frameworks. If you want to go deeper down the rabbit hole, simply follow the links and see how the best image segmentation models are built.

Happy segmenting!


This article was originally posted by Derrick Mwiti on the Neptune blog where you can find more in-depth articles for machine learning practitioners.