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We propose the adaptive scene dependent filter (ASDF) hierarchy for unsupervised learning of image segmentation, which integrates several processing pathways into a flexible, highly dynamic, and real-time capable vision architecture.
We introduce a method for automated threshold selection for adaptive scene partitioning schemes.
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According to Holden [ 6], the use of mixed reality, which combines physical and virtual environments, in rehabilitation training can provide adaptive scenes for interactive practice and feedback that engage the patient physically and mentally.
Therefore, the developed unified DEDR-VA-NN framework puts in a single optimization frame, radar/SAR image formation, speckle reduction, and adaptive dynamic scene image enhancement/fusion performed in the rapidly convergent NN-adapted computational fashion.
The joint modeling enables us to devise a novel scene adaptive and signal adaptive quantization that fully exploits the coding redundancies resulting from wavelet transform.
Adaptive threshold setting for the scene change detection method is preferable for robust detection performance, and so this remains as a future study.
We also compared the proposed adaptive scheme with the scene-adaptive method proposed in [9].
Hence, the reconstruction process is self-calibrated and adaptive to the scene.
Robust and discriminant feature fusion adaptive to camera scene changes for human tracking over camera networks.
In terms of the above unsolved technical challenges of tracking human over camera networks, future research directions on human tracking over camera networks can be summarized as follows: 1) Robust and discriminant feature fusion adaptive to camera scene changes for human tracking over camera networks.
Interestingly, this might better describe the running scene of adaptive divergence in El Faiyum Depression.
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