Unsupervised domain adaptation using feature aligned maximum classifier discrepancy (FAMCD)

The code implementation of our 2022 work on "Unsupervised domain adaptation using feature aligned maximum classifier discrepancy", by Prasanna Reddy Pulakurthi, Sohail A. Dianat, Majid Rabbani, Suya You, and Raghuveer M. Rao. [PDF]

Datasets

Digits Datasets

1. MNIST
2. USPS
3. SVHN

Results

Digits Datasets

Citation

Please consider citing our paper in your publications if it helps your research. The following is a BibTeX reference.

@inproceedings{pulakurthi2022unsupervised,
author = {Prasanna Reddy Pulakurthi and Sohail A. Dianat and Majid Rabbani and Suya You and Raghuveer M. Rao},
title = {{Unsupervised domain adaptation using feature aligned maximum classifier discrepancy}},
volume = {12227},
booktitle = {Applications of Machine Learning 2022},
editor = {Michael E. Zelinski and Tarek M. Taha and Jonathan Howe},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {1222707},
keywords = {Unsupervised Domain Adaptation, Adversarial Training, Multi-Classifier Structure, Maximum Classifier Discrepancy, Maximum Entropy},
year = {2022},
doi = {10.1117/12.2646422},
URL = {https://doi.org/10.1117/12.2646422}
}