Applying Class Incremental Learning

Job Description:

My project is to add new custom dataset to the original one Incrementally.

For example, I want to add new class while preserving other classes from previous model. The output will be a new class with the original one.

To be clear, I have two classes named ( permanent teeth, primary teeth, and filling).

Model 1 trained on PERM dataset ( single class)

Model 2 used pre-trained from model 1 to train new class (PRIM dataset). The output should be ( two classes, PERM & PRIM).

Model 3 used pre-trained from model 2 to train new class ( filling). The output after this model should be 3 classes and so on.

I want to tackle the problem of catastrophic forgetting.


1. Using Mask RCNN or U-Net versions ( TF & Keras)

2. Applied the continual learning approach similar to the attached (Class Incremental Learning)

3. Evaluate the mAP or others and accuracy for each class once we have more than one class.

some research papers:

- [login to view URL]

- [login to view URL]

- [login to view URL]:znrvB90XAY7wzof8iordssWWj2HPJSBBU7MjG-OHCy2Hn0IMsQsS7LbnKlT5ucaaKmBOh_XPSAR3&tag=1

Skills: Deep Learning, Python, Keras, Tensorflow, Image Processing

About the Client:
( 1 review ) Kansas City, United States

Project ID: #36259587

16 freelancers are bidding on average $189 for this job


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(26 Reviews)

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Experienced in tensorflow and MLOps, can have a look on the resources and help out on the requirements

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Hi there! I'm interested in your project to add new custom datasets incrementally to the original one, using Mask RCNN or U-Net versions (TF & Keras) and applying a continual learning approach. I have experience in imp More

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