… First, when computing the node embedding, instead of only aggregating messages computed
from a node’s local network neighbourhood, we allow P-GNNs to aggregate messages …

… We show that the knowledge-aware graph neural networks and label smoothness …
regularization on knowledge-aware graph neural networks. We apply the proposed method to four …

… systems and technologies and examine the relevant topics concerning communication and
network technologies, concepts, techniques … the broadband satellite systems, more intensive …

… systems and techniques. To overcome this drawback, fusion-based positioning of multiple
systems and/or techniques … -based indoor positioning techniques and systems from seminal …

… To address the above issues, we present a novel and practical deep architecture for video
person re-identification termed self-and-collaborative attention network (SCAN), which adopts …

… In addition, current methods lack an effective scheme to … filter network to solve the above
problems from three aspects: first, by weakening the high response features, we aim to identify …

… ML) techniques which include supervised, unsupervised, semi-supervised and reinforcement
[9]. We identify their key benefits and highlight VANET areas where they can be applied. …

… Inspired by graph convolutional networks (GCN)1 that try to … Networks (KGCN) for
recommender systems. The key idea of KGCN is to aggregate and incorporate neighborhood in…

… In Section IV, we discuss the evaluation methods of intrusion detection for in-vehicle networks
and comparatively analyze existing technologies. Section V summarizes the current trend …

… With the advancement of deep neural networks and increasing demand of intelligent video
… community. By dissecting the involved components in developing a person Re-ID system, we …