Quantum Neural Networks (QNNs) are an emerging technology that can be used in many applications including computer vision. In this paper, we presented a traffic sign classification system implemented using hybrid quantum-classical convolutional neural network. Experiments on the German Traffic Sign Recognition Benchmark dataset indicate currently QNN do not outperform classical DCNN (Deep Convo...

Reliable network traffic classification is essential to management and security tasks. Therefore, it beneficial analyze improve existing techniques. Some of the most traditional methodologies for are based on port number packet payload, each which presents an increasing set problems. Port number-based techniques suffer from misuse numbers tunneling. This primarily due their reliance proper use ...

Network Traffic Classification is an important process in various network management activities like network planning, designing, workload characterization etc. Network traffic classification using traditional techniques such as well known port number based and payload analysis based techniques are no more effective because various applications uses port hopping and encryption technique to avoi...