Because of the nature of earthwork, there are difficulties in improving productivity due to situational variability and task complexity. Therefore, automation is receiving attention as a method to improve productivity...
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Because of the nature of earthwork, there are difficulties in improving productivity due to situational variability and task complexity. Therefore, automation is receiving attention as a method to improve productivity. This study was conducted as a part of the IES (Intelligent Excavator System). The IES (Intelligent Excavator System) is intended for development of unmanned and remote controlled excavation systems for earthwork. The purpose of this study was to develop algorithms to merge two models acquired by a 3D laser scanner and Stereovision system in real time. To develop accurate and fast merging algorithms, ICP (Iterative Closest Point)-based merging algorithms and normal vectors were applied. algorithms to merge the two models and to reflect the characteristics of the necessary earthwork will be proposed. (C) 2013 Elsevier B.V. All rights reserved.
This paper proposes an effective subtree merging based data collection algorithm for wireless sensor networks (WSNs), named as SMDC algorithm, which can be applied in a new kind of applications in WSNs, i.e., area que...
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This paper proposes an effective subtree merging based data collection algorithm for wireless sensor networks (WSNs), named as SMDC algorithm, which can be applied in a new kind of applications in WSNs, i.e., area query application. The SMDC algorithm can prevent unnecessary energy consumption in ancestor nodes for routing through the union of disjoint sets for different subtrees in the network. The SMDC algorithm includes four phases. Firstly the cluster trees are constructed respectively in the target area. Then the disjoint node sets for each subtrees will be found;thirdly the disjoint subtrees are connected via the closest node between two subtrees;and the last phase is to disconnect the subtrees which have been connected to a new tree branch from their previous tree structure. This paper also presents the simulation to compare the SMDC algorithm with some related works including conventional minimum spanning tree algorithm. Simulation results show that the SMDC algorithm can reduce the redundant energy consumption and the number of hops which results in the reduction of total energy consumption. Especially, it is more efficient as the number of sensor nodes in a target area increases.
This paper makes the following contributions: 1) A compact trie representation and a hybrid data structure for IP lookup that reduces the memory consumption while eliminating backtracking. 2) A merging algorithm that ...
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ISBN:
(纸本)9780769543017
This paper makes the following contributions: 1) A compact trie representation and a hybrid data structure for IP lookup that reduces the memory consumption while eliminating backtracking. 2) A merging algorithm that eliminates leaf pushing and simplifies table updates in virtual routers.
Face detection is a useful technique in computer vision. Many face detectors have been developed in the literature. These detectors to evaluate a face likelihood of a given sub-window. The sub-window must be scanned t...
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ISBN:
(纸本)9788995003848
Face detection is a useful technique in computer vision. Many face detectors have been developed in the literature. These detectors to evaluate a face likelihood of a given sub-window. The sub-window must be scanned through an input image to detect faces. Since the detectors evaluate the scanned sub-windows independently, non-faces with high face likelihood are often misdetected. In this paper, we propose a novel face detection algorithm which explicitly uses difference of face likelihood distribution between faces and non-faces. The proposed algorithm can correctly classify the non-faces misdetected by the existing algorithm. The face likelihood distribution is generated and integrated to emphasize the difference between faces and non-faces. Experiments with pre-scanned data set and real-world images show that the proposed algorithm improves the detection rate approximately 20% and 10%, respectively.
A new algorithm is developed to merge a high-resolution panchromatic image and a low-resolution multispectral image based on the combination of multiresolution wavelet decomposition, evolutionary strategy and the IHS ...
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ISBN:
(纸本)0780386531
A new algorithm is developed to merge a high-resolution panchromatic image and a low-resolution multispectral image based on the combination of multiresolution wavelet decomposition, evolutionary strategy and the IHS transform. The high-resolution panchromatic image is firstly decomposed to the wavelet planes, then the regions are partitioned by evolutionary strategy in terms of difference of edge information from wavelet planes and the merging algorithm is done by adding edge influence factor in different region. The proposed method is compared with the IHS and the MWT methods. The results of the comparison show the proposed merger performing the best in combining and preserving spectral-spatial infonnation for the test images.
In this paper, we propose a merging algorithm, which can provide efficient support for multipoint-to-point ABR service in ATM networks. By forwarding the FRM cells belonging to the VC with the largest FRM-cell arrival...
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In this paper, we propose a merging algorithm, which can provide efficient support for multipoint-to-point ABR service in ATM networks. By forwarding the FRM cells belonging to the VC with the largest FRM-cell arrival rate in a merge point, the proposed algorithm can achieve better link utilization than existing merging algorithms. In addition, the proposed algorithm reduces the number of FRM cells forwarded by a C merge point. As a result, it can reduce the control overhead of ABR service. Most importantly, it does not incur extra complexity in switches. We also discuss the impact of different network topologies on our algorithm. Simulation results show that the proposed algorithm is able to achieve better performance while requiring significantly fewer RM cells. (C) 2001 Elsevier Science B.V. All rights reserved.
Image segmentation is fundamental to many image analysis problems. It aims to partition a digital image into a set of nonoverlapping homogeneous regions. The main contribution of this paper is the development of a new...
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Image segmentation is fundamental to many image analysis problems. It aims to partition a digital image into a set of nonoverlapping homogeneous regions. The main contribution of this paper is the development of a new segmentation procedure which is designed to segment images corrupted by correlated noise. This new segmentation procedure is based on Rissanen's minimum description length (MDL) principle and consists of two components: i) an MDL-based criterion in which the "best" segmentation is defined as its minimizer and ii) a merging algorithm which attempts to locate this minimizer. The performance of this procedure is illustrated via a simulation study, with promising results.
In this article we describe a parallel algorithm which applies Givens rotations to selectively annihilate k(k + 1)/2 nonzero elements from two k x n(k less-than-or-equal-to n) upper trapezoidal submatrices. The new al...
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In this article we describe a parallel algorithm which applies Givens rotations to selectively annihilate k(k + 1)/2 nonzero elements from two k x n(k less-than-or-equal-to n) upper trapezoidal submatrices. The new algorithm we propose is suitable for implementation on either a pair of directly connected local-memory processors or two clusters of multiple tightly-coupled processors. Our analyses show that in both cases the proposed algorithms achieve optimal speed-up by balancing the work load distribution and masking inter-processor or inter-cluster communication by computation if k << n. In the context of solving large scale least squares problems [1,4], this submatrix merging step is repetitively needed during the entire computation and, furthermore, there are usually many pairs of such submatrices to be merged with each submatrix stored in the memory of a processor or a cluster of processors. The proposed algorithm can be applied to each pair of submatrices concurrently and thus parallelizes an important step in solving the least squares problems.
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