Results 191 to 200 of about 444,086 (291)

Deviation‐Guided Attention for Semi‐Supervised Anomaly Detection With Contrastive Regularisation

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Anomaly detection (AD) aims to identify abnormal patterns that deviate from normal behaviour, playing a critical role in applications such as industrial inspection, medical imaging and autonomous driving. However, AD often faces a scarcity of labelled data. To address this challenge, we propose a novel semi‐supervised anomaly detection method,
Guanglei Xie   +6 more
wiley   +1 more source

Deep memory for deep threats: A novel architecture combining GRUs and deep learning models for IDS. [PDF]

open access: yesPLoS One
Alqhatani A   +5 more
europepmc   +1 more source

MSFFNet: Multiscale Feature Fusion Network for Small Target Detection in Remote Sensing Images

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the advancement of satellite remote sensing technology, object detection based on high‐resolution remote sensing imagery has emerged as a prominent research focus in the field of computer vision. Although numerous algorithms have been developed for remote sensing image object detection, they still suffer from challenges such as low ...
Hui Zong   +5 more
wiley   +1 more source

Dynamic Resource Allocation Optimisation and Security‐Resilient Control for Bandwidth‐Limited Network Control Systems With Data Conflicts

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Networked control systems (NCSs) often suffer from performance degradation due to limited communication bandwidth, which can cause data transmission conflicts and packet loss. Existing scheduling strategies may fail to simultaneously meet the real‐time requirements and the importance of multisensor data, and they are particularly vulnerable ...
Da Chen   +5 more
wiley   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu   +4 more
wiley   +1 more source

Blockchain-based secure MEC model for VANETs using hybrid networks. [PDF]

open access: yesSci Rep
Goud GV   +5 more
europepmc   +1 more source

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