kahnchana/opl
Official repository for "Orthogonal Projection Loss" (ICCV'21)
This project offers a novel method to enhance the performance of deep learning models in image classification and related tasks. It takes standard image datasets with labels as input and produces more robust and accurate classification models by improving how the model separates different classes. Anyone working with image recognition, especially in fields requiring high accuracy or handling limited data, would find this beneficial.
129 stars. No commits in the last 6 months.
Use this if you are developing image classification models and need to improve accuracy, especially when dealing with domain generalization, few-shot learning, or robustness against adversarial attacks and noisy labels.
Not ideal if your primary goal is not image classification or if you are working with unsupervised learning tasks, as it's currently focused on supervised classification.
Stars
129
Forks
19
Language
Python
License
MIT
Category
Last pushed
Nov 29, 2021
Commits (30d)
0
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