Haifeng Li

Frequent Itemset Mining Algorithm based on Sampling Method

2016 · Advances in computer science research

Frequent itemset mining is an important technique in data mining. This paper employ the sampling method to improve the performance. An in-memory index is presented to store the data information, which is maintained by our …

A Heuristic Rule Based Approximate Frequent Itemset Mining Algorithm

2016 · Procedia Computer Science

In this paper, we focus on the problem of mining the approximate frequent itemsets. To improve the performance, we employ a sampling method, in which a heuristic rule is used to dynamically determine the sampling …

Memory-Contrastive Unsupervised Domain Adaptation for Building Extraction of High-Resolution Remote Sensing Imagery

2023 · IEEE Transactions on Geoscience and Remote Sensing

Deep learning-based semantic segmentation has been widely applied for building extraction. However, due to the domain gap, the extraction of building in high-resolution remote sensing imagery is difficult when the model trained on a source …

Modern synergetic neural network for imbalanced small data classification

2023 · Scientific Reports

Deep learning's performance on the imbalanced small data is substantially degraded by overfitting. Recurrent neural networks retain better performance in such tasks by constructing dynamical systems for robustness. Synergetic neural network (SNN), a synergetic-based recurrent …

A Region-Adaptive Local Perturbation-Based Method for Generating Adversarial Examples in Synthetic Aperture Radar Object Detection

2024 · Remote Sensing

In synthetic aperture radar (SAR) imaging, intelligent object detection methods are facing significant challenges in terms of model robustness and application security, which are posed by adversarial examples. The existing adversarial example generation methods for …