IEEE/ACM TRANSACTIONS ON NETWORKING 1 Robust Network Traffic Classification —As a fundamental tool for network management and security, traffic classification has attracted increasing attention in recent years. A significant challenge to the robustness of classification performance comes from zero-day applic...
CLASSIFICATIONObjectives: Recognition of mobile applications within encrypted network traffic holds considerable effects across multiple domains, encompassing network administration, security, and digital marketing. The creation of network traffic classifiers capable of adjusting to dynamic and unforeseeable real-...
Anomalies in packet length sequences caused by network topology structure and congestion greatly impact the performance of early network traffic classification. Additionally, insufficient differentiation of packet length sequences using a small number of packets also affects the performance. In this letter,...
Study of network traffic classification and application identification网络流量分类与应用识别的研究* This paper introduced the different levels of traffic analysis and relevant knowledge of machine learning,and analyzed some problems in traffic classificat... LIU Yingqiu,LI Wei,LI Yunchun,... - 《计算...
(2) For the experiments on Traffic-QA [11], we extract the frame-level video motion and appearance features using the pretrained 3D ResNeXt-101 and ResNet-101, respectively. Each video is uniformly sampled into eight clips. The word-level query features are first extracted from Glove and ...
In view of this, an attempt is made to propose a robust online learning ship tracking algorithm based on the Siamese network and the region proposal network. Firstly, the algorithm combines the off-line Siamese network classification score and the online classifier score for discriminative learning,...
an intertwined neural network model for eeg classification in brain-computer interfaces [Paper] machine learning-based eeg applications and markets [Paper] bayesian pseudo labels: expectation maximization for robust and efficient semi-supervised segmentation [Paper] deformation equivariant cross-modalit...
Cromvik and Patriksson (2010b) apply results on the robustness of stochastic mathematical programs with equilibrium constraints to intensity-modulated radiation therapy, in addition to traffic network design. Further, Chen et al. (2011) proposes a robust optimization approach for managing hospital beds...
Multimodal vehicle type classification using convolutional neural network and statistical representations of MFCC Recognition of vehicle types in real life traffic scenarios is a challenging task due to the diversity of vehicles and uncontrolled environments. Efficient... B Selbes,M Sert - IEEE Internatio...
Adaptive graph convolutional recurrent network for traffic forecasting Larochelle H., Ranzato M., Hadsell R., Balcan M., Lin H. (Eds.), Advances in Neural Information Processing Systems, Vol. 33, Curran Associates, Inc. (2020), pp. 17804-17815 ...