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ConNet: Deep Semi-Supervised Anomaly Detection Based on Sparse Positive Samples

机译：连接：基于稀疏阳性样本的深度半监督异常检测

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Feng Gao; Jing Li; Ruiying Cheng; Yi Zhou; Ying Ye;
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年度 2021
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1. An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos [J] . B. Ravi Kiran, Dilip Mathew Thomas, Ranjith Parakkal Journal of Imaging . 2018,第2期

机译：基于深度学习的视频中无监督和半监督异常检测方法的概述
2. Semi-supervised sparse representation classifier (S~3RC) with deep features on small sample sized hyperspectral images [J] . Aydemir M. Said, Bilgin Gokhan Neurocomputing . 2020,第Jul25期

机译：半监控稀疏表示分类器（S〜3RC），小型样本大小高光谱图像深度特征
3. A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data [J] . Xiao Yawen, Wu Jun, Lin Zongli, Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice . 2018,第期

机译：基于堆积稀疏自动编码器的半监督深度学习方法，使用RNA-SEQ数据进行癌症预测
4. Neural Batch Sampling with Reinforcement Learning for Semi-supervised Anomaly Detection [C] . Wen-Hsuan Chu, Kris M. Kitani European Conference on Computer Vision . 2020

机译：具有钢筋学习的神经批量抽样，用于半监督异常检测
5. Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning. [D] . Valko, Michal. 2011

机译：基于自适应图的算法，用于条件异常检测和半监督学习。
6. EvAn: Neuromorphic Event-Based Sparse Anomaly Detection [O] . Lakshmi Annamalai, Anirban Chakraborty, Chetan Singh Thakur 2021

机译：Evan：基于神经形态的事件稀疏异常检测
7. An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos [O] . Kiran, B Ravi, Thomas, Dilip Mathew, Parakkal, Ranjith 2018

机译：基于深度学习的无监督和无人值守方法综述视频中的半监督异常检测

ConNet: Deep Semi-Supervised Anomaly Detection Based on Sparse Positive Samples

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