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个人信息Personal Information
教授 博士生导师
性别：男
毕业院校：电子科技大学
学历：博士研究生毕业
学位：工学博士学位
在职信息：在职人员
所在单位：计算机科学与工程学院（网络空间安全学院）
学科：计算机科学与技术
办公地点：主楼B1-601
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- [21] 刘沛 ， 5S通信：DSCA: A dual-stream network with cross-attention on whole-slide image pyramids for cancer prognosis， Expert Systems with Applications， vol. 227， pp. 120280， Oct 2023.
- [22] 2S作者：GraphLSurv: A Scalable Survival Prediction Network with Adaptive and Sparse Structure Learning for Histopathological Whole-Slide Images， Computer Methods and Programs in Biomedicine， vol. 231， pp. 107433， Apr 2023.
- [23] 3S通信：SANet: Spatial Attention Network with Global Average Contrast Learning for Infrared Small Target Detection，ICASSP 2023，2023.02，accepted
- [24] 4S通信：AugTarget Data Augmentation for Infrared Small Target Detection，ICASSP 2023，2023.02，accepted
- [25] 3S通信：Geometry Attention Transformer with position-aware LSTMs for image captioning, Expert Systems with Applications, 2022.04, 117174.
- [26] 纪禄平 , Recurrent Convolutions of Binary-constraint Cellular Neural Network for Texture Recognition, Neurocomputing, vol. 387, pp. 161-171, Jan 2020.
- [27] 纪禄平 , Training-based Gradient LBP Feature Models for Multi-resolution Texture Classification, IEEE Transactions on Cybernetics, vol. 48, no. 9, pp. 2683-2696, Sep 2018.
- [28] 纪禄平 , Median Local Ternary Patterns Optimized with Rotation-invariant Uniform-three Mapping for Noisy Texture Classification, Pattern Recognition, vol. 79, pp. 387-401, Jul 2018.
- [29] 纪禄平 , One-dimensional Pairwise CNN for the Global Alignment of Two DNA Sequences, Neurocomputing, vol. 149, pp. 505-514, Feb 2015.
- [30] 纪禄平 , Fingerprint Orientation Field Estimation Using Ridge Projection, Pattern Recognition, vol. 41, no. 5, pp. 1508-1520,
- [31] 纪禄平 , An Improved Pulse Coupled Neural Network Model for Image Processing, Neural Computing and Applications, vol. 17, no. 3, pp. 255-263,
- [32] 纪禄平 , A Mixed Noise Image Filtering Method Using Weighted-Linking PCNNs, Neurocomputing, vol. 71, pp. 2986-3000,
- [33] 纪禄平 , Binary Fingerprint Image Thinning using Template-based PCNNs, IEEE Transactions on Systems, Man, and Cybernetics, Part B, Cybernetics, vol. 37, no. 5, pp. 1407-1413,