… anomaly detection is a time-critical application of computer vision, we explore the anomaly
detection using edge … The confluence of edge computing and anomaly detection for real-time …

… account and ignore the correlation anomalies between the data from multi… anomaly detection
model in distributed edge computing. Then, the Edge Computing based Anomaly Detection …

… data anomaly detection method based on edge computing is proposed. Firstly, an edge
computing … , and according to the computing capabilities of different types of devices, anomaly …

… an adaptive anomaly detection approach for hierarchical edge computing (HEC) systems
to solve this problem. Specifically, we first construct three anomaly detection DNN models of …

… for detection of the above-mentioned anomalies and also supports mobile edge computing
(… real call detail record (CDR) dataset for anomaly detection. Our framework achieved 98.8% …

… While the general architecture is similar to what we present in this paper, we apply
federated learning to the anomaly detection task in an edge computing environment. …

… of edge computing and deep learning, we propose a vehicle anomaly detection method
based on edge computing and deep learning. We first designed the edge processing layer to …

… the consumption without loss in detection performance, we introduce the edge computing
method in our implementation. That is to transfer some steps into the edge application in the …

… off-loading the data to the edge. We demonstrate our solution for a widely used anomaly
detection algorithm, windowed Gaussian anomaly detector and evaluate the performance of the …

… enhanced real-time detection of anomalous data in IoT … anomaly detection scheme with
hierarchical edge computing (HEC). Specifically, we first construct multiple anomaly detection …