Exact(8)
Distraction osteogenesis is widely used for the treatment of various challenging musculoskeletal disorders.
These observations are verified from the experimental results of various challenging datasets.
The proposed methodology is successfully validated on various challenging multi-component reactive flow configurations.
It can be shown that our method adapts to partial occlusion and various challenging cases.
This enables the method to achieve good robustness and precision in identifying salient objects in videos under various challenging conditions.
An optimized DES performance is desirable to successfully treat various challenging coronary lesions in a broad population of patients.
In order to make the algorithm robust to various challenging appearance changes, we adopt the powerful deep features in the description of tracking object appearance.
The experimental results reveal that the proposed method is more effective and robust than the state-of-the-art trackers on various challenging sequences.
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