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In addition, the recognition of building elements from the point clouds solely relied on their spatial features.
The second study tested the recognition of building elements in the 3D point cloud with their visual recognition cues.
It was noted that the use of visual recogniton cues could facilitate the recognition of building elements in 3D.
This provides good reference to the policy makers, the building owners, and to the China and Hong Kong Governments when considering reciprocal recognition of building energy codes.
The results show that a high degree of automation could be achieved for the registration of building scenes captured from different scans and the recognition of building elements with the proposed framework.
Compared with the point cloud based methods, the recognition of building elements from color images or videos can be performed using multiple recognition cues, which could increase the recognition accuracy.
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Another outcome of the recognition of importance of building networks with CBOs on the cognitive dimension had ceiling effects at baseline scores.
Similar results were found for the participants with lower baseline scores for the recognition of importance of building networks with CBOs.
Although many recognition methods have been developed, the robust recognition of buildings elements has not been achieved yet.
The additional analyses showed that an advantage of this intervention program would be raising the level of the recognition of the importance of building interorganizational networks with CBOs as well as recognition of the knowledge of skills required to do so.
Similarly, the attendees of the program with lower baseline scores on recognition of the importance of building an interorganizational network with CBOs came to recognize the importance of this after the intervention to a greater degree than those who did not attend.
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Justyna Jupowicz-Kozak
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