Class Incremental Learning using PyTorch for Image Segmentation NOT Classification

I am looking for a freelancer who has advanced experience with PyTorch to help me with my project on Class Incremental Learning for Image Segmentation. The purpose of the project is for research purposes. Requirements: - Implement a class incremental learning algorithm using PyTorch - Develop a model that can learn new classes without forgetting the previously learned ones - The model should be able to incrementally learn new classes and improve its performance over time - Implement a memory mechanism to store previous knowledge and utilize it for future learning - Ensure the model can handle a large number of classes without a significant drop in performance Ideal Skills and Experience: - Advanced experience with PyTorch and deep learning frameworks - Strong understanding of class incremental learning algorithms and techniques - Knowledge of memory mechanisms and how to implement them in deep learning models - Familiarity with handling small and medium datasets and training models on them - Ability to work independently and deliver high-quality code If you have a list of requirements and are experienced with PyTorch, please reach out to discuss the project further. I am open to suggestions and would appreciate your expertise in defining the project's functionalities. Dataset: My dataset is x-ray images, and the annotation is a JSON file for each class (coco format). I have three classes (permanent teeth as PERM, primary teeth as PRIM, and filling). If you have the necessary skills and experience in Python programming, image segmentation algorithms, and class incremental learning techniques, and are interested in working on this project, please submit your proposal.