Among qualitative direction relation models, Oriented point relation algebra(OPRAm) is a remarkable model for robot navigation with uncertain direction information. It has great advantages in providing powerful expr...
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Among qualitative direction relation models, Oriented point relation algebra(OPRAm) is a remarkable model for robot navigation with uncertain direction information. It has great advantages in providing powerful expressions with very limited information compared with other point-based spatial relation *** original OPRAm is defined in 2D space, and its model and reasoning algorithm are found not applicable in 3D space. We proposed a novel direction relation model named OPRA3Dmto extend the original OPRAm to 3D space,and presented a new reasoning algorithm on Oriented point relation algebra in three dimension(OPRA3Dm). A further study was carried out for composition reasoning on OPRA3Dm. The proposed reasoning algorithm will deduce new information which cannot be directly detected by hardware. The experiment showed the algorithm had some practical significance, it can be applied to the Unmanned aerial vehicle(UAV) navigation and similar scenarios.
The servo motor’s flexible acceleration/deceleration(acc/dec) control is an emerging research topic in the automation field. A velocity control algorithm based on trigonometric function is proposed in this *** requir...
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The servo motor’s flexible acceleration/deceleration(acc/dec) control is an emerging research topic in the automation field. A velocity control algorithm based on trigonometric function is proposed in this *** required parameters, it transforms trigonometric calculations into elementary mathematical operations and calculates the velocity controlling values iteratively, which could avoid trigonometric calculation and reduce the computation time. Experimental results show that the proposed algorithm is suitable for implementation on field programmable gate arrays and achieves a flexible controlling, enhancing both the equipment’s stability and reliability. It is promising to significantly improve the high-speed computerized numerical control equipment’s controlling accuracy, without a huge hardware resource consumption.
In the fields of social network analysis and knowledge graph, many semi-supervised learning algorithms based on graph convolutional neural network (GCN) have been widely used. Most of these algorithms usually improve ...
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The paper is concerned with the improvement of the rational representation theory for solving positive-dimensional polynomial systems. The authors simplify the expression of rational representation set proposed by Tan...
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The paper is concerned with the improvement of the rational representation theory for solving positive-dimensional polynomial systems. The authors simplify the expression of rational representation set proposed by Tan and Zhang(2010), obtain the simplified rational representation with less rational representation sets, and hence reduce the complexity for representing the variety of a positive-dimensional ideal. As an application, the authors compute a "nearly" parametric solution for the SHEPWM problem with a fixed number of switching angles.
Measuring word semantic similarity is a generic problem with a broad range of applications such as ontology mapping, computational linguistics and artificial intelligence. Previous approaches to computing word semanti...
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Measuring word semantic similarity is a generic problem with a broad range of applications such as ontology mapping, computational linguistics and artificial intelligence. Previous approaches to computing word semantic similarity did not consider concept occurrence frequency and word’s sense number. This paper introduced Hyponymy graph, and based on which proposed a novel word semantic similarity model. For two words to be compared, we first retrieve their related concepts; then produce lowest common ancestor matrix and distance matrix between concepts; finally calculate distance-based similarity and information-based similarity, which are integrated to get final semantic similarity. The main contribution of our method is that both concept occurrence frequency and word’s sense number are taken into account. This similarity measurement more closely fits with human rating and effectively simulates human thinking process. Our experimental results on benchmark dataset M&C and R&G with Word Net2.1 as platform demonstrate roughly 0.9%–1.2%improvements over existing best approaches.
This paper studies semantic segmentation primarily under image-level weak-supervision. Most stateof-the-art technologies have recently used deep classification networks to create small and sparse discriminatory seed r...
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This paper studies semantic segmentation primarily under image-level weak-supervision. Most stateof-the-art technologies have recently used deep classification networks to create small and sparse discriminatory seed regions of each interest target as pseudo-labels for training segmentation networks, which achieve inferior performance compared with the fully supervised *** propose a Dilated convolutional pixels affinity network(DCPAN) to localize and expand the seed regions of objects to bridge this gap. Although introduced dilated convolutional units enable capture of additional location information of objects, it falsely highlighted true negative regions as dilated rate enlarge. To address this problem,we properly integrate dilated convolutional units with different dilated rates and self-attention mechanisms to obtain pixel affinity measure matrix for promoting classification network to generate high-quality object seed regions as pseudo-labels; thus, the performance of the segmentation network is boosted. Furthermore,although our approach seems simple, our method obtains a competitive performance, and experiments show that the performance of DCPAN outperforms other state-ofart approaches in weakly-supervised settings, which only use image-level labels on the Pascal VOC 2012 dataset.
In this paper we propose an algorithm of computing minimal diagnosis based on BDD (Binary Decision Diagram). First we give the concept of disjunction equations, and map the collection of conflict sets into disjunction...
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This paper presents a biologically inspired local image descriptor that combines color and shape features. Compared with previous descriptors, red-cyan cells associated with L, M, and S cones (L for long, M for mediu...
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This paper presents a biologically inspired local image descriptor that combines color and shape features. Compared with previous descriptors, red-cyan cells associated with L, M, and S cones (L for long, M for medium, and S for short) are used to indicate one of the opponent color channels. Stepping forward from state-of-the-art color feature extraction, we exploit a new approach to compute the color orientation and magnitudes of three opponent color channels, namely, red-green, blue-yellow, and red-cyan, in two-dimensional space. Color orientation is calculated in histograms with magnitude weighting. We linearly concatenate the four-color-opponent-channel histogram and scale-invariant-feamre-transform histogram in the final step. We apply our biologically inspired descriptor to describe the local image feature. Quantitative comparisons with state-of-the-art descriptors demonstrate the significant advantages of maintaining invariance to photometric and geometric changes in image matching, particularly in cases, such as illumination variation and image blurring, where more color contrast information is observed.
To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this syste...
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To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.
The main purpose of this paper is to investigate the connection between the Painlev′e property and the integrability of polynomial dynamical systems. We show that if a polynomial dynamical system has Painlev′e prope...
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The main purpose of this paper is to investigate the connection between the Painlev′e property and the integrability of polynomial dynamical systems. We show that if a polynomial dynamical system has Painlev′e property, then it admits certain class of first integrals. We also present some relationships between the Painlev′e property and the structure of the differential Galois group of the corresponding variational equations along some complex integral curve.
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