纪禄平

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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论文成果

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[1] 2S通信：Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology，accepted， ICLR 2025， pp. 1-8， Jan 2025.
[2] 2S通信：Spatial-Temporal-Channel Collaborative Feature Learning with Transformers for Infrared small target Detection， Image and Vision Computing， vol. 154， pp. 1-12， Jan 2025.
[3] 2S通信：Moving Infrared Dim and Small Target Detection by Spatio-temporal Mixed Encoding， Engineering Applications of Artificial Intelligence， vol. 144， pp. 1-12， Jan 2025.
[4] 2S通信：WSOE: Weakly Supervised Outlier Exposure for Object-level Out-of-distribution Detection， Expert Systems With Applications， vol. 270， pp. 1-15， Jan 2025.
[5] 2S通信：Semi-supervised Multi-view Prototype Learning with Motion Reconstruction for Moving Infrared Small Target Detection， IEEE Trans. on Geoscience and Remote Sensing， vol. 63， pp. 1-15， Jan 2025.
[6] 2S通信：Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classification, Proceedings of the AAAI Conference on Artificial Intelligence, 39(3), 3158-3166， AAAI 2025， Apr 2025.
[7] 2S通信：Mining In-distribution Attributes in Outliers for Out-of-distribution Detection, Proceedings of the AAAI Conference on Artificial Intelligence, 39(17), 18181-18188， AAAI 2025， Apr 2025.
[8] 2S通信：Motion Prior Knowledge Learning with Homogeneous Language Descriptions for Moving Infrared Small Target Detection, Proceedings of the AAAI Conference on Artificial Intelligence, 39(2), 2186-2194， AAAI 2025， Apr 2025.
[9] 2S通信：Spatio-temporal fusion with motion masks for the moving small target detection from remote-sensing videos， Engineering Applications of Artificial Intelligence， vol. 138， no. Part A， pp. 1-12， Sep 2024.
[10] 2S通信：Triple-domain Feature Learning with Frequency-aware Memory Enhancement for Moving Infrared Small Target Detection， IEEE Transactions on Geoscience and Remote Sensing， vol. 62， pp. 1-14， Aug 2024.
[11] 2S通信：Towards Dense Moving Infrared Small Target Detection: New Datasets and Baseline， IEEE Transactions on Geoscience and Remote Sensing， vol. 62， pp. 1-13， Aug 2024.
[12] 2S通信：TMP: Temporal Motion Perception with spatial auxiliary enhancement for moving Infrared dim-small target detection， Expert Systems with Applications， vol. 255，Part C， pp. 124731， Jul 2024.
[13] 2S通信：Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation， the Forty-first International Conference on Machine Learning (ICML 2024)， vol. 235， pp. 31262-31292， May 2024.
[14] 2S通信：MICPL: Motion-Inspired Cross-Pattern Learning for Small Object Detection in Satellite Videos， IEEE Transactions on Neural Networks and Learning Systems， vol. 36， no. 4， pp. 6437-6450， Apr 2025.
[15] 3S通信：ProDiv：Prototype-driven consistent pseudo-bag division for whole-slide image classification， Computer Methods and Programs in Biomedicine， vol. 249， pp. 1-9， Apr 2024.
[16] 2S通信：Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification， IEEE Transactions on Medical Imaging， vol. 43， no. 5， pp. 1841-1852， Jan 2024.
[17] 2S通信：SSTNet: Sliced spatio-temporal network with cross-slice ConvLSTM for moving infrared dim-small target detection， IEEE Transactions on Geoscience and Remote Sensing， vol. 62， pp. 1-12， Jan 2024.
[18] 2S通信：AdvMIL: Adversarial multiple instance learning for the survival analysis on Whole-slide image， Medical Image Analysis， vol. 91， pp. 103020， Jan 2024.
[19] 2S通信：Multi-scale LBP fusion with the contours from deep CellNNs for texture classification， Expert Systems with Applications， vol. 238,Part D， pp. 122100， Oct 2023.
[20] 2S通信：Shared Coupling-bridge Scheme for Weakly Supervised Local Feature Learning，online， IEEE Transactions on Multimedia， May 2023.

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