Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

With the rapid advancements of sensor technology and deep learning, autonomous driving
systems are providing safe and efficient access to intelligent vehicles as well as intelligent …

Ship detection from synthetic aperture radar (SAR) images is inherently subject to the
special imaging mechanism of SAR. In recent years, deep-learning-based techniques for …

Speech Emotion Recognition (SER) plays a significant role in the field of Human–Computer
Interaction (HCI) with a wide range of applications. However, there are still some issues in …

Multitarget detection is very challenging, especially when targets are densely distributed. In
conventional constant false alarm rate (CFAR) detection algorithms, the detection threshold …

Orthogonal Time Frequency Space (OTFS) is a new, promising modulation waveform
candidate for the next-generation integrated sensing and communication (ISaC) systems …

In this article, the concept of quantile is introduced and elaborately related to the truncation
depth, based on which quantile truncated statistics (QTS) is put forward. The QTS gives a …

The presented paper is further focused on the presentation and subsequent assessment of
utilising a proposed Neural Network (NN) with simple architecture in the role of a signal …

Current methods for radar target detection usually work on the basis of high signal-to-clutter
ratios. In this paper we propose a novel convolutional neural network based dual-activated …

With the widespread connectivity of everyday devices realized by the advent of the Internet
of Things (IoT), communication between users of different devices has become increasingly …