DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot Learning

[PDF] arxiv.org

FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification

K Fu, X Luo, L Qu, S Wang, Y Xiong… - arXiv preprint arXiv …, 2024 - arxiv.org
The expensive fine-grained annotation and data scarcity have become the primary
obstacles for the widespread adoption of deep learning-based Whole Slide Images (WSI) …
被引用次数：1 相关文章 所有 4 个版本

Multi-scale task-aware structure graph modeling for few-shot image recognition

P Zhao, Z Ye, L Wang, H Liu, X Ji - Pattern Recognition, 2024 - Elsevier
The Few-shot image recognition attempts to recognize images from a novel class with only a
limited number of labeled training images, which is a few-shot learning (FSL) task. FSL is …
相关文章 所有 3 个版本

BRAVE: A cascaded generative model with sample attention for robust few shot image classification

H Ji, L Luo, H Peng - Neurocomputing, 2024 - Elsevier
Few-shot learning (FSL) confronts notable challenges due to the disparity between training
and testing categories, leading to channel bias in neural networks and hindering accurate …
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[PDF] arxiv.org

Meta-UAD: A Meta-Learning Scheme for User-level Network Traffic Anomaly Detection

T Feng, Q Qi, L Guo, J Wang - arXiv preprint arXiv:2408.17031, 2024 - arxiv.org
Accuracy anomaly detection in user-level network traffic is crucial for network security.
Compared with existing models that passively detect specific anomaly classes with large …
相关文章 所有 2 个版本