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Table 2 presents the performance of object representation.
Therefore, this dataset is applicable to test the performance of object labeling.
The performance of object tracking may be worse due to these differences.
However, many of existing object proposal generators have pool localization quality, which weakens the performance of object detectors.
Recently, low-cost RGB-D sensors (e.g., Microsoft Kinect) have been widely used to complement RGB data with depth, helping to improve significantly performance of object detection.
Our experimental results demonstrate that this approach can significantly improve the efficiency of feature representation and the performance of object recognition with occlusion.
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Analyzing the performance of object-based storage services is a task, which has been addressed by several other works.
Thus, a dynamic adaptive mechanism for object-tracking tree can improve the performance of object-tracking tree.
To improve performance of object-oriented query processing, a careful and intelligent skew handling for load balancing must be established.
The studies by Van Zyl et al. [42] and Kopteff [34] compare the performance of Java ORM-frameworks to the performance of Object-databases.
From the discussion in previous section, we know that a dynamic adaptive mechanism for object-tracking tree can improve the performance of object-tracking tree.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com