… number of abnormal samples. However, machine learning algorithms and deep learning
methods, such as Naive Bayes (NB) and Convolutional Neural Networks (CNN), are difficult to …

… the detection scheme for APT attack has three schemes: sandbox scheme, network anomaly
… Comparison with the results of other deep learning methods 表2. 与其他深度学习方法的结果…

… In the last decade, deep learning has been proved to be successful … deep learning models
showed their powerful learning abilities, such as Deep Convolutional Neural Network, Deep …

… us with promising ways to investigate the law of ship motions and the detection of abnormal
behaviours. In this paper, various algorithms used for detecting abnormal behaviours of ship …

… forecast members based on supervised machine learning with application to runoff …
different rainfall return periods based on deep learning and data warehouse. Science of the …

… , we are releasing our deep learning model that will allow … detection, and provide feedback
to us on ways to improve the classifier. Our general purpose Caffe deep neural network …

… of abnormal behavior. For cases of being more than safety threshold value, using the isolated
forest detection … , and thus find abnormal data to achieve the detection effect. Experiments …

… A deep learning-based approach to progressive vehicle re-identification for urban
surveillance[C]//Proceedings of the European Conference on Computer Vision, Amsterdam, Oct8-16, …

… data anomalies identification method based on feature extraction and pattern recognition
neural network (… , and the operation time is only one-tenth of the time of deep learning methods. …

… in the field of network anomaly detection. In comparison to … the field of flow data in network
anomaly detection. [Literature Scope] … methods, machine learning methods, and deep learning …