EDNFC-Net is a CNN architecture for nuclei-instance segmentation. The architecture utilizes a fundamental building block called FCC and uses intra-FCC as well as inter-FCC features concatenation. The architecture is trained with a loss function that encourages better foreground and background separation. The full article is available [here]. The BibTeX citation of the article is as follows:
@INPROCEEDINGS{9053633,
author={S. {Gehlot} and A. {Gupta} and R. {Gupta}},
booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={EDNFC-Net: Convolutional Neural Network with Nested Feature Concatenation for Nuclei-Instance Segmentation},
year={2020},
pages={1389-1393},}
author={S. {Gehlot} and A. {Gupta} and R. {Gupta}},
booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={EDNFC-Net: Convolutional Neural Network with Nested Feature Concatenation for Nuclei-Instance Segmentation},
year={2020},
pages={1389-1393},}