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Entropy guided multi level feature fusion network for high precision content based image retrieval. [PDF]
Sci RepLavanya M +3 more
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Self-Generative Multi-View Skeleton Feature Fusion for Isolated Sign Language Recognition
Peiyun Xue +7 more
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Automatic EEG artifact detection using a local-global feature fusion network in time and time-frequency domains. [PDF]
Acta EpileptolYu Q, Lin C, Wang W, Feng Z, Wen M.
europepmc +1 more source
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IEE Proceedings - Radar, Sonar and Navigation, 1996
A centralised plot-level data fusion technique, which is based on a neural network, is presented. A self-organised feature-mapping technique, which learns from sensor observations, is used to integrate the data from several sensors with various unknown measurement accuracies.
F. Wang +4 more
openaire +1 more source
A centralised plot-level data fusion technique, which is based on a neural network, is presented. A self-organised feature-mapping technique, which learns from sensor observations, is used to integrate the data from several sensors with various unknown measurement accuracies.
F. Wang +4 more
openaire +1 more source
SPIE Proceedings, 1999
This paper describes two practical fusion techniques for automatic target cueing that combine features derived from each sensor data ta the object-level. In the hybrid fusion method each of the input sensor data is prescreened before the fusion stage. The cued fusion method assumes that one of the sensors is designated as a primary sensor, and thus ATC
Tamar Peli +4 more
openaire +1 more source
This paper describes two practical fusion techniques for automatic target cueing that combine features derived from each sensor data ta the object-level. In the hybrid fusion method each of the input sensor data is prescreened before the fusion stage. The cued fusion method assumes that one of the sensors is designated as a primary sensor, and thus ATC
Tamar Peli +4 more
openaire +1 more source