GSoC 2021 project idea 3.1: Upgrading DevoLearn

Devolearn is a Python package that aims to automate the process of collecting metadata from videos/images of the C. elegans embryo with the help of deep learning models. It is specialized for the analysis of 2-D slices of C. elegans embryogenesis.

This project will focus on improving the performance of existing models and training/benchmarking new models on a broad range of data sets from different species relevant to developmental biology. Your goals will be to improve overall performance of the models in terms of accuracy and generalizability, training/adding new models and improve the library’s usability.

There would be 4 key elements in this project:

  • Improving the current models
  • Training and adding more useful models
  • Improving usability
  • (optional) Interactive online demos.

Improving/adding new models
In order to get good performance from a deep-learning model, we should use techniques like:

  • k-fold cross validation
  • Ensembling/stacking
  • Hyperparameter optimization
  • Label smoothing
  • Mixed precision inference
  • Using more training data for re-training the pre-existing models for better accuracy

Improving usability
As the library grows, we should have a better place to host proper documentation on a static website. We also have to train devolearn’s deep-learning models on commonly available data, the more common the use case, the more helpful it is to the community.

Online demos
Jupyter notebooks, however simple they may seem, are still a bit intimidating to people from non CS backgrounds, so there should be a focus on making interactive and easy to run online demos which showcase both our research and tutorials.

Pre-requisites
Proficiency in python with a good hold of tools like numpy, pandas and PyTorch will be required.

Resources

More information can be found at: Proposals-Public-Lectures/upgrading-devolearn.md at master · devoworm/Proposals-Public-Lectures · GitHub

Mentors: Bradly Alicea, Mayukh Deb

Tags: DevoWorm, Python, microscopy, deep learning, data science

2 Likes

I am very interested in collaborating on this project

1 Like

Hey, @malin, I have done some projects with the help of deep learning models. So, have a previous experience with them. I found this project to be much similar with what I have done previously, just need some time to get familiar with code base. Please let me know how to start, till then I will have a look at the code base and other documentries.

Hi @Athene-ai @Kartik-Khandelwal, glad to know that you’re interested. I suggest you to join our slack to get in touch with us.

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Dear @malin which is the specific channel of the project on slack? :slightly_smiling_face:

@Athene-ai We work mostly on the #devolearn channel, and sometimes the #devoworm channel as well

perfect ! :slight_smile:

Not sure, but I recommend to look for the main channel or the welcome channels (#general, #townhall, #welcome) and ask

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