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Human-Machine Cooperative Video Anomaly Detection
Liming (Luke) Chen
School of Computing
Faculty Of Computing, Eng. & Built Env.
Research output
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Contribution to journal
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Article
›
peer-review
93
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Dive into the research topics of 'Human-Machine Cooperative Video Anomaly Detection'. Together they form a unique fingerprint.
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Social Sciences
video
71%
final judgment
49%
Human Uses
43%
neural network
38%
event
36%
performance
29%
reconstruction
28%
surveillance
27%
expert
20%
Group
9%
Engineering & Materials Science
Anomaly detection
100%
Feedback
60%
Convolutional neural networks
43%
Computer vision
40%