The Active Segmentation platform for ImageJ (ASP/IJ) was developed in the scope of GSOC 2016 - 2018. The plugin provides a general-purpose environment that allows biologists and other domain experts to use transparently state-of-the-art techniques in machine learning to achieve excellent image segmentation. ImageJ is a public domain Java image processing program extensively used in life and material sciences. The program was designed with an open architecture that provides extensibility via plugins.
The project idea: The existing machine learning model of Active Segmentation is based on the Weka library. However, this is limited to traditional machine learning approaches. The objective of the project will be to incorporate deep-learning functionality into the platform. Deep neural nets are capable of record-breaking accuracy. The candidate will explore existing implementations, for example Deeplearning4j or Neuroph. Next, the candidate will select a library to be incorporated into ASP/IJ and will provide a reference implementation.
● Fix existing issues and bugs
● Add-on to the user interface for trajectory display
● Provide a reference implementation
Minimal set of deliverables
● Requirement specification - Prepared by the candidate after understanding the functionality.
● System Design - Detailed plan for the development of the plugin and test cases.
● Implementation and testing - Details of implementation and testing of the platform.
Desired skills: Java, machine learning
Mentors: Dimiter Prodanov (firstname.lastname@example.org ), INCF Belgian Node; (backup) Sumit Vohra, ZIB, Berlin, Germany
- ImageJ: https://imagej.nih.gov/
- Weka https://www.cs.waikato.ac.nz/ml/weka/
- Active Segmentation : https://github.com/sumit3203/ACTIVESEGMENTATION
I am Dhiraj Sharma from Army Institute of Technology, Pune currently in final year in Electronics and Telecommunication branch.
I have been contributing to opensource since last year and i was gsoc,gci mentor for coala and public lab organisations.
Recently i was selected as top 16 developers for summer of code in space program organised by european space agency where my project was based on java to implement conditional replenishment algorithm and motion compensation for prediction of solar flares images.
I have been contributing to opensource since last year and this time i am looking to join gsoc as a student.
Can i get some pointers on how to start immediately and develop draft proposal?
Also, do i need previous contribution too?
Hello Dhiraj, I am tagging @dprodanov who is the mentor for this project, he will get back to you. /Malin, org admin
Alright, mam thank you for the reply.
We have a Github resource, which I post here:
The GSOC 2018 project
The GSOC 2017 project
@dprodanov Do I need prior contributions for this project or should I directly start with my development and build a proposal once i get started on my local machine?
Pleaase get familiar with ImageJ in terms of functionality.
Once you have done that you can study the Active Segmentation and build a proposal.
Alright, thank you for this information sir.I have started learning it to get familiar.
Hi @dprodanov and @malin, I was interested in contributing to this project. I have worked on deep learning modules prior to this and have a good understanding on deep learning fundamentals. How can I get started?
@dprodanov Hi should we contribute in terms of bugs and issue or start with the proposal?
What tasks should I ideally work on for a successful proposal?
Hi @codeboy5, We will appreciate very much testing and signaling of issues.
There is a stable master version. The latest branch (Bordeaux) is under code clean up.
Greetings for the day!
Hello I am Raghavendra Singh Chauhan,a prefinal year electronics engineering student.I have been working on signal processing in my graduation discipline.I hope I would be able to contribute effectively in this regard to this project with my knowledge of core Java and signal processing.
What technologies except ImageJ would you suggest so that I could prepare myself better for handling this project efficiently?
You should get familiar with the Weka library.
Thank you so much for the advice.
I would surely be familiarising myself with it.
I’m Joanna, 1st year CSE student from TU Delft and a fourth year medical student. I’m very interested in this project. Previously I’ve been working on image segmenation using CNNs in radiology. I read your advice in terms of getting familiar with ImageJ, Weka, and Active Segmentation and I was wondering what are your most pressing issues with Active Segmentation at this moment/what are you focusing on at the very moment/ what do you expect us to work on (except for testing obviously) before building our proposal. Thanks a lot for your reply!
Thank you very much for your interest. Please contact me for the proposal template.
I am Satyam sharma, an AI engineer/Researcher specialized in Deep Learning and Natural language processing and a Data scientist specialized in data analytics and machine learning.
With working on 10+ Real-world projects in different fields of Deep learning including Image segmentation, Image augmentation, object detection, image multi-classification, image multi labeling, OCR, etc of different domains like medical, education, finance, manufacturing,
In my work, I have also worked with building very large scalable systems that are powered by deep learning maintaining efficiency, performance, and accuracy.
My experience includes everything from using
- Frameworks like Tensorflow, PyTorch, Keras
- Pre-trained models and state of art models
- Building Custom models
- Implementing models from Research papers
- Building pipelines
- communication and leading internal teams
- collecting, cleaning, analyzing and visualizing data.
Having in-depth knowledge and different skill sets to offer to this project, i would love to be a part of the Team and help it reach new heights.
- ImageJ: completed reviewing
- Weka: Had a glance over it
- I need help with the template
Any pointers on what should I do next? @dprodanov
Thanks for reading such a long text, so patiently,
Thank you very much for your interest. Please contact me by e-mail for the application template.