Fusion-CAM: Segmentation Pseudo-label Generation using the Multiple Instance Learning Choquet Integral
** NOTE: THIS REPO IS STILL UNDER CONSTRUCTION. THE CODE WILL BE UPDATED SOON TO BE MORE USER-FRIENDLY.
Connor McCurley
In this repository, we provide a Python implementation of the Fusion-CAM algorithm.
The assiciated papers for this repository are:
This code uses standard anaconda libraries.
To recursively clone this repository using Git, use the following command:
git clone --recursive https://github.com/GatorSense/fusion-cam.git
This source code is licensed under the license found in the LICENSE file in the root directory of this source tree.
This product is Copyright (c) 2022 C.McCurley, and A. Zare. All rights reserved.
If you use the Fusion-CAM algorithm, please cite the following references using the following entry.
Plain Text:
C. McCurley, "Discriminatve Feature Learning with Imprecise, Uncertain, and Ambiguous Data," Ph.D Thesis, Gainesville, FL, 2022.
BibTex:
@phdthesis{mccurley2022thesis,
author={C. McCurley},
title={Discriminative Feature Learning with Imprecise, Uncertain, and Ambiguous Data},
school={Univ. of Florida},
year={2022},
address={Gainesville, FL},
}
Also check out our Multiple Instance Choquet Integral (MICI) algorithm for information fusion!
For any questions, please contact:
Alina Zare
Email Address: azare@ece.ufl.edu
University of Florida, Department of Electrical and Computer Engineering