All Outputs (4)

FU-Net: Multi-class Image Segmentation Using Feedback Weighted U-Net (2019)
Book Chapter
Jafari, M., Li, R., Xing, Y., Auer, D., Francis, S., Garibaldi, J., & Chen, X. (2019). FU-Net: Multi-class Image Segmentation Using Feedback Weighted U-Net. In Image and Graphics: 10th International Conference, ICIG 2019, Beijing, China, August 23–25, 2019, Proceedings, Part II (529-537). Springer Verlag. https://doi.org/10.1007/978-3-030-34110-7_44

© 2019, Springer Nature Switzerland AG. In this paper, we present a generic deep convolutional neural network (DCNN) for multi-class image segmentation. It is based on a well-established supervised end-to-end DCNN model, known as U-net. U-net is firs... Read More about FU-Net: Multi-class Image Segmentation Using Feedback Weighted U-Net.

Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation (2019)
Book Chapter
Hou, X., Liu, J., Xu, B., Liu, B., Chen, X., Garibaldi, J., …Qiu, G. (2019). Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation. In Medical Image Computing and Computer Assisted Intervention – MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II (101-109). Springer Verlag. https://doi.org/10.1007/978-3-030-32245-8_12

Supervised semantic segmentation normally assumes the test data being in a similar data domain as the training data. However, in practice, the domain mismatch between the training and unseen data could lead to a significant performance drop. Obtainin... Read More about Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation.

A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets (2019)
Conference Proceeding
Shen, Z., Chen, X., & Garibaldi, J. M. (2019). A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2019.8858890

In this paper, we propose a novel weighted combination feature selection method using bootstrap and fuzzy sets. The proposed method mainly consists of three processes, including fuzzy sets generation using bootstrap, weighted combination of fuzzy set... Read More about A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets.

Performance Optimization of a Fuzzy Entropy Based Feature Selection and Classification Framework (2019)
Conference Proceeding
Shen, Z., Chen, X., & Garibaldi, J. (2019). Performance Optimization of a Fuzzy Entropy Based Feature Selection and Classification Framework. . https://doi.org/10.1109/SMC.2018.00238

© 2018 IEEE. In this paper, based on a fuzzy entropy feature selection framework, different methods have been implemented and compared to improve the key components of the framework. Those methods include the combinations of three ideal vector calcul... Read More about Performance Optimization of a Fuzzy Entropy Based Feature Selection and Classification Framework.