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Several approaches to resolving the salient object detection problem consist of two steps: saliency map extraction and salient object localization.
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Two important prerequisites to build and test dynamic transportation network vulnerability assessment algorithms are (i) map extraction tools and (ii) an accurate network demand profile to test algorithms on these maps.
The latter includes region-of-interest selection, 2D Fast Fourier Transform for range-Doppler map extraction, peak detection and alarm decision logic.
Three main computational entities of ant-agent, seed extractor and algorithm library are designed and road map updating is performed through three main stages of verification of the old map, extraction of possible roads and grouping of the results of both stages.
RDH having great performance on DE and HS techniques to retain location map, extraction information, image restoration and overflow/underflow problems [17].
The analysis of connected components is mainly used for many automated image processing applications such as object extraction, road map extraction, line detection, etc. Connected components can be extracted using morphological operations.
Figure 2 illustrates our simulation tool chain from the map extraction to the output of the vehicle trajectory dump: We extracted a road map from OpenStreetMap via jOSM, which we converted with the SUMO tool netconvert to a network file.
Disparity map extraction of an image is a computationally demanding task.
Considering that disparity map extraction of an image is a computationally demanding task, practical real-time FPGA based algorithms require increased device utilization resource usage, depending on the disparity levels operational range, which leads to significant power consumption.
We present two semi-automatic depth map extraction methods for stereo video conversion.
The outdoor reflection glare has a negative impact on the depth map extraction.
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