Shuyue Guan
Orcid: 0000-0002-3779-9368
According to our database1,
Shuyue Guan
authored at least 29 papers
between 2017 and 2024.
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Bibliography
2024
Restorable Synthesis: Average Synthetic Segmentation Converges to a Polygon Approximation of an Object Contour in Medical Images.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2024
2023
CFPNet-M: A light-weight encoder-decoder based network for multimodal biomedical image real-time segmentation.
Comput. Biol. Medicine, March, 2023
Effect of color-normalization on deep learning segmentation models for tumor-infiltrating lymphocytes scoring using breast cancer histopathology images.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
The training accuracy of two-layer neural networks: its estimation and understanding using random datasets.
Proceedings of the 52nd IEEE Applied Imagery Pattern Recognition Workshop, 2023
2022
Int. J. Artif. Intell. Tools, 2022
CaraNet: context axial reverse attention network for segmentation of small medical objects.
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Informing selection of performance metrics for medical image segmentation evaluation using configurable synthetic errors.
Proceedings of the 51st IEEE Applied Imagery Pattern Recognition Workshop, 2022
2021
A novel measure to evaluate generative adversarial networks based on direct analysis of generated images.
Neural Comput. Appl., 2021
CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects.
CoRR, 2021
DC-UNet: rethinking the U-Net architecture with dual channel efficient CNN for medical image segmentation.
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
An Optimized Weak Target Recognition Method Based on Transform Domain with Strong Background Noise.
Proceedings of the CAA Symposium on Fault Detection, 2021
A Sneak Attack on Segmentation of Medical Images Using Deep Neural Network Classifiers.
Proceedings of the 50th IEEE Applied Imagery Pattern Recognition Workshop, 2021
2020
The estimation of training accuracy for two-layer neural networks on random datasets without training.
CoRR, 2020
CoRR, 2020
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation.
CoRR, 2020
Data Separability for Neural Network Classifiers and the Development of a Separability Index.
CoRR, 2020
Measures to Evaluate Generative Adversarial Networks Based on Direct Analysis of Generated Images.
CoRR, 2020
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020
Analysis of Generalizability of Deep Neural Networks Based on the Complexity of Decision Boundary.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020
Understanding the Ability of Deep Neural Networks to Count Connected Components in Images.
Proceedings of the 49th IEEE Applied Imagery Pattern Recognition Workshop, 2020
2019
Proceedings of the 48th IEEE Applied Imagery Pattern Recognition Workshop, 2019
Evaluation of Generative Adversarial Network Performance Based on Direct Analysis of Generated Images.
Proceedings of the 48th IEEE Applied Imagery Pattern Recognition Workshop, 2019
2018
Proceedings of the Medical Imaging 2018: Biomedical Applications in Molecular, 2018
Breast cancer detection using synthetic mammograms from generative adversarial networks in convolutional neural networks.
Proceedings of the 14th International Workshop on Breast Imaging, 2018
Segmentation of Thermal Breast Images Using Convolutional and Deconvolutional Neural Networks.
Proceedings of the 47th IEEE Applied Imagery Pattern Recognition Workshop, 2018
2017
Proceedings of the 2017 IEEE Applied Imagery Pattern Recognition Workshop, 2017