| A comprehensive overview of image enhancement techniques Y Qi, Z Yang, W Sun, M Lou, J Lian, W Zhao, X Deng, Y Ma Archives of Computational Methods in Engineering, 1-25, 2021 | 40 | 2021 |
| Multi-level nested pyramid network for mass segmentation in mammograms R Wang, Y Ma, W Sun, Y Guo, W Wang, Y Qi, X Gong Neurocomputing 363, 313-320, 2019 | 39 | 2019 |
| Heterogeneous SPCNN and its application in image segmentation Z Yang, J Lian, S Li, Y Guo, Y Qi, Y Ma Neurocomputing 285, 196-203, 2018 | 29 | 2018 |
| ARF-Net: An Adaptive Receptive Field Network for breast mass segmentation in whole mammograms and ultrasound images C Xu, Y Qi, Y Wang, M Lou, J Pi, Y Ma Biomedical Signal Processing and Control 71, 103178, 2022 | 15 | 2022 |
| A new heterogeneous neural network model and its application in image enhancement Y Qi, Z Yang, J Lian, Y Guo, W Sun, J Liu, R Wang, Y Ma Neurocomputing 440, 336-350, 2021 | 15 | 2021 |
| A fire-controlled MSPCNN and its applications for image processing J Lian, Z Yang, W Sun, L Zheng, Y Qi, B Shi, Y Ma Neurocomputing 422, 150-164, 2021 | 14 | 2021 |
| MCRNet: Multi-level context refinement network for semantic segmentation in breast ultrasound imaging M Lou, J Meng, Y Qi, X Li, Y Ma Neurocomputing 470, 154-169, 2022 | 12 | 2022 |
| Morph_SPCNN model and its application in breast density segmentation Y Qi, Z Yang, J Lei, J Lian, J Liu, W Feng, Y Ma Multimedia Tools and Applications 80, 2821-2845, 2021 | 12 | 2021 |
| Adaptive channel and multiscale spatial context network for breast mass segmentation in full-field mammograms W Zhao, M Lou, Y Qi, Y Wang, C Xu, X Deng, Y Ma Applied Intelligence, 1-18, 2021 | 10 | 2021 |
| BASCNet: Bilateral adaptive spatial and channel attention network for breast density classification in the mammogram W Zhao, R Wang, Y Qi, M Lou, Y Wang, Y Yang, X Deng, Y Ma Biomedical Signal Processing and Control 70, 103073, 2021 | 9 | 2021 |
| MGBN: Convolutional neural networks for automated benign and malignant breast masses classification M Lou, R Wang, Y Qi, W Zhao, C Xu, J Meng, X Deng, Y Ma Multimedia Tools and Applications 80 (17), 26731-26750, 2021 | 9 | 2021 |
| FS-UNet: Mass segmentation in mammograms using an encoder-decoder architecture with feature strengthening J Pi, Y Qi, M Lou, X Li, Y Wang, C Xu, Y Ma Computers in Biology and Medicine 137, 104800, 2021 | 8 | 2021 |
| Breast density analysis based on glandular tissue segmentation and mixed feature extraction X Gong, Z Yang, D Wang, Y Qi, Y Guo, Y Ma Multimedia Tools and Applications 78, 31185-31214, 2019 | 8 | 2019 |
| Multi-scale attention-guided network for mammograms classification C Xu, M Lou, Y Qi, Y Wang, J Pi, Y Ma Biomedical Signal Processing and Control 68, 102730, 2021 | 6 | 2021 |
| Multi-level feature fusion network for nuclei segmentation in digital histopathological images X Li, J Pi, M Lou, Y Qi, S Li, J Meng, Y Ma The Visual Computer 39 (4), 1307-1322, 2023 | 3 | 2023 |
| Aggregated pyramid attention network for mass segmentation in mammograms M Lou, Y Qi, X Li, C Xu, W Zhao, X Deng, Y Ma Multimedia Tools and Applications 81 (10), 13335-13353, 2022 | 3 | 2022 |
| A high speed pseudo-random bit generator driven by 2D-discrete hyperchaos Z Yang, Y Liu, Y Wu, Y Qi, F Ren, S Li Chaos, Solitons & Fractals 167, 113039, 2023 | 2 | 2023 |
| A Hyper-Chaotically Encrypted Robust Digital Image Watermarking Method with Large Capacity Using Compress Sensing on a Hybrid Domain Z Yang, Q Sun, Y Qi, S Li, F Ren Entropy 24 (10), 1486, 2022 | 2 | 2022 |
| Learning multi-frequency features in convolutional network for mammography classification Y Wang, Y Qi, C Xu, M Lou, Y Ma Medical & Biological Engineering & Computing 60 (7), 2051-2062, 2022 | 2 | 2022 |
| DCANet: Dual contextual affinity network for mass segmentation in whole mammograms M Lou, Y Qi, J Meng, C Xu, Y Wang, J Pi, Y Ma Medical Physics 48 (8), 4291-4303, 2021 | 2 | 2021 |
Dr.Yide MaProfessor of school information science and engineering, Lanzhou University在 lzu.edu.cn 的电子邮件经过验证
Dr.Yide MaProfessor of school information science and engineering, Lanzhou University在 lzu.edu.cn 的电子邮件经过验证