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Journal articles on the topic 'Coarse-to-fine search'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

Korah, Reeba, and J. Raja Paul Perinba . "A Novel Coarse-to-fine Search Motion Estimator." Information Technology Journal 5, no. 6 (2006): 1073–77. http://dx.doi.org/10.3923/itj.2006.1073.1077.

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Godwin, Hayward J., Erik D. Reichle, and Tamaryn Menneer. "Coarse-to-fine eye movement behavior during visual search." Psychonomic Bulletin & Review 21, no. 5 (2014): 1244–49. http://dx.doi.org/10.3758/s13423-014-0613-6.

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Over, E. A. B., I. T. C. Hooge, B. N. S. Vlaskamp, and C. J. Erkelens. "Coarse-to-fine eye movement strategy in visual search." Vision Research 47, no. 17 (2007): 2272–80. http://dx.doi.org/10.1016/j.visres.2007.05.002.

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Beck, M. R., and M. C. Lohrenz. "Coarse-to-Fine Search Strategy when Searching in Clutter." Journal of Vision 11, no. 11 (2011): 1324. http://dx.doi.org/10.1167/11.11.1324.

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Atiquzzaman, M. "Coarse-to-Fine Search Technique to Detect Circles in Images." International Journal of Advanced Manufacturing Technology 15, no. 2 (1999): 96–102. http://dx.doi.org/10.1007/s001700050045.

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Ogawa, H., and T. Kumada. "Coarse-to-fine encoding of contextual information in visual search." Journal of Vision 5, no. 8 (2005): 945. http://dx.doi.org/10.1167/5.8.945.

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Kawamata, Koji, and Kenta Oku. "Roadscape-based Route Recommender System Using Coarse-to-fine Route Search." Journal of Information Processing 27 (2019): 392–403. http://dx.doi.org/10.2197/ipsjjip.27.392.

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Raharjo, Jangkung, Adi Soeprijanto, and Hermagasantos Zein. "Multi Dimension of Coarse to Fine Search Method Development for Solving Economic Dispatch." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 1 (2016): 1. http://dx.doi.org/10.11591/ijeecs.v3.i1.pp1-9.

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<p>Economic dispatch problem has grown along with the development of electric power business, for example in a competitive electric power business that offers electrical energy in the form of the step function, non-differentiable function. This is not a continuous function so there is no guarantee that those methods can execute the optimization problem well, especially the Lagrange and Direct methods. There are the non-differentiable functions within the optimization will become a challenge that should be solved. This paper proposes Coarse to Fine Search method development to solve the p

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Fu, Hu Dai, Hua Wang, and Jin Gang Gao. "Circles Detection in Images by Using of Coarse-to-Fine Search Technique." Applied Mechanics and Materials 220-223 (November 2012): 1385–88. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1385.

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In the automatic production, the application of machine vision technology on image pattern recognition is an important task. Realistic image is composed of these basic units such as straight lines, circles and ellipses. But the actual images usually contain noise and other interferences. So the images will have some discontinuous modes. Hough transform is commonly used to detect straight lines, circles or other parametric patterns in noisy images. In practical application, Hough transform requires a large amount of storage space and computation. In the paper, it proposed an efficient coarse-to

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Kim, Chansu, Donghui Song, Chang-Su Kim, and Sung-Kee Park. "Object tracking under large motion: Combining coarse-to-fine search with superpixels." Information Sciences 480 (April 2019): 194–210. http://dx.doi.org/10.1016/j.ins.2018.12.042.

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Mallot, Hanspeter A., Sabine Gillner, and Petra A. Arndt. "Is correspondence search in human stereo vision a coarse-to-fine process?" Biological Cybernetics 74, no. 2 (1996): 95–106. http://dx.doi.org/10.1007/s004220050222.

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Mallot, Hanspeter A., Sabine Gillner, and Petra A. Arndt. "Is correspondence search in human stereo vision a coarse-to-fine process?" Biological Cybernetics 74, no. 2 (1996): 95–106. http://dx.doi.org/10.1007/bf00204198.

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Chen, Xi, Yaping Wu, Guohua Zhao, et al. "Automatic Histogram Specification for Glioma Grading Using Multicenter Data." Journal of Healthcare Engineering 2019 (December 19, 2019): 1–12. http://dx.doi.org/10.1155/2019/9414937.

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Multicenter sharing is an effective method to increase the data size for glioma research, but the data inconsistency among different institutions hindered the efficiency. This paper proposes a histogram specification with automatic selection of reference frames for magnetic resonance images to alleviate this problem (HSASR). The selection of reference frames is automatically performed by an optimized grid search strategy with coarse and fine search. The search range is firstly narrowed by coarse search of intraglioma samples, and then the suitable reference frame in histogram is selected by fi

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Cheng, Fei, Kai Liu, Mao-Guo Gong, Kaiyuan Fu, and Jiangbo Xi. "Robust visual tracking via randomly projected instance learning." International Journal of Intelligent Computing and Cybernetics 10, no. 3 (2017): 258–71. http://dx.doi.org/10.1108/ijicc-11-2016-0052.

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Purpose The purpose of this paper is to design a robust tracking algorithm which is suitable for the real-time requirement and solves the mistake labeling issue in the appearance model of trackers with the spare features. Design/methodology/approach This paper proposes a tracker to select the most discriminative randomly projected ferns and integrates a coarse-to-fine search strategy in this framework. First, the authors exploit multiple instance boosting learning to maximize the bag likelihood and select randomly projected fern from feature pool to degrade the effect of mistake labeling. Seco

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Lin, Zhao Hua, Xin Liu, Yu Liang Zhang, and Shu Mei Zhang. "An Auto-Focus Algorithm of Fast Search Based on Combining Rough and Fine Adjustment." Advanced Materials Research 468-471 (February 2012): 534–37. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.534.

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A coarse and fine combined fast search and auto-focusing algorithm was suggested in this paper. This method can automatically search and find the focal plane by evaluating the image definition. The Krisch operator based edge energy function was used as the big-step coarse focusing, and then the wavelet transform based image definition evaluation function, which is sensitivity to the variation in image definition, was used to realize the small-step fine focusing in a narrow range. The un-uniform sampling function of the focusing area selection used in this method greatly reduces the workload an

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CHEN, JIANYONG, QIUZHEN LIN, and QINGBIN HU. "APPLICATION OF NOVEL CLONAL ALGORITHM IN MULTIOBJECTIVE OPTIMIZATION." International Journal of Information Technology & Decision Making 09, no. 02 (2010): 239–66. http://dx.doi.org/10.1142/s0219622010003804.

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In this paper, a novel clonal algorithm applied in multiobjecitve optimization (NCMO) is presented, which is designed from the improvement of search operators, i.e. dynamic mutation probability, dynamic simulated binary crossover (D-SBX) operator and hybrid mutation operator combining with Gaussian and polynomial mutations (GP-HM) operator. The main notion of these approaches is to perform more coarse-grained search at initial stage in order to speed up the convergence toward the Pareto-optimal front. Once the solutions are getting close to the Pareto-optimal front, more fine-grained search is

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Li, Li, Joon Wayn Cheong, Jinghui Wu, and Andrew G. Dempster. "Improvement to Multi-resolution Collective Detection in GNSS Receivers." Journal of Navigation 67, no. 2 (2013): 277–93. http://dx.doi.org/10.1017/s0373463313000635.

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Collective detection is a promising approach to positioning in a weak signal environment, in which the navigation solution is directly obtained by acquisition search in a multi-dimensional position and common clock bias uncertainty space. By combining the correlation values from multiple satellites and fully utilizing the coherence between them, the detectable C/N0 of individual satellites can be lowered. However, the lack of a computationally efficient optimization algorithm due to high dimensionality and complexity has hindered its application. A multi-resolution collective detection is ther

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Atkinson, Janette, and Oliver J. Braddick. "‘Where’ and ‘What’ in Visual Search." Perception 18, no. 2 (1989): 181–89. http://dx.doi.org/10.1068/p180181.

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A line segment target can be detected among distractors of a different orientation by a fast ‘preattentive’ process. One view is that this depends on detection of a ‘feature gradient’, which enables subjects to locate where the target is without necessarily identifying what it is. An alternative view is that a target can be identified as distinctive in a particular ‘feature map’ without subjects knowing where it is in that map. Experiments are reported in which briefly exposed arrays of line segments were followed by a pattern mask, and the threshold stimulus-mask interval determined for three

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Ben, Guangli, Xifeng Zheng, Yongcheng Wang, Ning Zhang, and Xin Zhang. "A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal." Applied Sciences 11, no. 2 (2021): 673. http://dx.doi.org/10.3390/app11020673.

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A local search Maximum Likelihood (ML) parameter estimator for mono-component chirp signal in low Signal-to-Noise Ratio (SNR) conditions is proposed in this paper. The approach combines a deep learning denoising method with a two-step parameter estimator. The denoiser utilizes residual learning assisted Denoising Convolutional Neural Network (DnCNN) to recover the structured signal component, which is used to denoise the original observations. Following the denoising step, we employ a coarse parameter estimator, which is based on the Time-Frequency (TF) distribution, to the denoised signal for

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Liagkouras, K., and K. Metaxiotis. "An Experimental Analysis of a New Interval-Based Mutation Operator." International Journal of Computational Intelligence and Applications 14, no. 03 (2015): 1550018. http://dx.doi.org/10.1142/s1469026815500182.

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In this paper, we present a novel Interval-Based Mutation (IBMU) operator. The proposed mutation operator is performing coarse-grained search at initial stage in order to speed up convergence toward more promising regions of the search landscape. Then, more fine-grained search is performed in order to guide the solutions towards the Pareto front. Computational experiments indicate that the proposed mutation operator performs better than conventional approaches for solving several well-known benchmarking problems.

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Zhang, Yu Dong, Le Nan Wu, Yuan Kai Huo, and Shui Hua Wang. "A Novel Global Optimization Method – Genetic Pattern Search." Applied Mechanics and Materials 44-47 (December 2010): 3240–44. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3240.

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A novel global optimization method is proposed to find global minimal points more effectively and quickly. The new algorithm is based on both genetic algorithms (GA) and pattern search (PS) algorithms, thus, we have named it genetic pattern search. The procedure involves two-phases: First, GA executes a coarse search, PS then executes a fine search. Experiments on four different test functions (consisting of Hump, Powell, Rosenbrock, and Woods) demonstrate that this proposed new algorithm is superior to improved GA and improved PS with respect to success rate and computation time. Therefore, g

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Ernst, Gidon, Sean Sedwards, Zhenya Zhang, and Ichiro Hasuo. "Falsification of Hybrid Systems Using Adaptive Probabilistic Search." ACM Transactions on Modeling and Computer Simulation 31, no. 3 (2021): 1–22. http://dx.doi.org/10.1145/3459605.

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We present and analyse an algorithm that quickly finds falsifying inputs for hybrid systems. Our method is based on a probabilistically directed tree search, whose distribution adapts to consider an increasingly fine-grained discretization of the input space. In experiments with standard benchmarks, our algorithm shows comparable or better performance to existing techniques, yet it does not build an explicit model of a system. Instead, at each decision point within a single trial, it makes an uninformed probabilistic choice between simple strategies to extend the input signal by means of explo

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Moussa, A., and N. Elsheimy. "AUTOMATIC REGISTRATION OF APPROXIMATELY LEVELED POINT CLOUDS OF URBAN SCENES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5 (August 19, 2015): 145–50. http://dx.doi.org/10.5194/isprsannals-ii-3-w5-145-2015.

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Registration of point clouds is a necessary step to obtain a complete overview of scanned objects of interest. The majority of the current registration approaches target the general case where a full range of the registration parameters search space is assumed and searched. It is very common in urban objects scanning to have leveled point clouds with small roll and pitch angles and with also a small height differences. For such scenarios the registration search problem can be handled faster to obtain a coarse registration of two point clouds. In this paper, a fully automatic approach is propos

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ZUO, AIQIU, JASON Z. ZHANG, KEVIN STANLEY, and Q. M. JONATHAN WU. "A HYBRID STEREO FEATURE MATCHING ALGORITHM FOR STEREO VISION-BASED BIN PICKING." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 08 (2004): 1407–22. http://dx.doi.org/10.1142/s0218001404003794.

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Stereo vision-based bin picking systems require accurate 3D information to be recovered from 2D stereo images. To achieve this goal, we have developed a hybrid coarse-to-fine algorithm for stereo feature matching, which is based on the 2D six-parameter affine transformation and local similarity evaluation. With this algorithm, the coarse matching is performed by the 2D six-parameter affine transformation to get rough feature matches, imposing a strong constraint to further search instead of the traditional epipolar constraint. To obtain precise matches, the perspective effect is dealt with fin

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Hou, Yi, Hong Zhang, and Shilin Zhou. "Tree-based indexing for real-time ConvNet landmark-based visual place recognition." International Journal of Advanced Robotic Systems 14, no. 1 (2017): 172988141668695. http://dx.doi.org/10.1177/1729881416686951.

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Recent impressive studies on using ConvNet landmarks for visual place recognition take an approach that involves three steps: (a) detection of landmarks, (b) description of the landmarks by ConvNet features using a convolutional neural network, and (c) matching of the landmarks in the current view with those in the database views. Such an approach has been shown to achieve the state-of-the-art accuracy even under significant viewpoint and environmental changes. However, the computational burden in step (c) significantly prevents this approach from being applied in practice, due to the complexi

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Lee, Donghun, Jongwon Kim, and TaeWon Seo. "Optimal design of 6-DOF eclipse mechanism based on task-oriented workspace." Robotica 30, no. 7 (2011): 1041–48. http://dx.doi.org/10.1017/s0263574711000774.

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SUMMARYWe present a new numerical optimal design for a redundant parallel manipulator, the eclipse, which has a geometrically symmetric workspace shape. We simultaneously consider the structural mass and design efficiency as objective functions to maximize the mass reduction and minimize the loss of design efficiency. The task-oriented workspace (TOW) and its partial workspace (PW) are considered in efficiently obtaining an optimal design by excluding useless orientations of the end-effector and by including just one cross-sectional area of the TOW. The proposed numerical procedure is composed

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Mei, Fang, Tianchang Gao, and Yingda Lyu. "CF Model: A Coarse-to-Fine Model Based on Two-Level Local Search for Image Copy-Move Forgery Detection." Security and Communication Networks 2021 (May 4, 2021): 1–13. http://dx.doi.org/10.1155/2021/6688393.

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Copy-move forgery is the most predominant forgery technique in the field of digital image forgery. Block-based and interest-based are currently the two mainstream categories for copy-move forgery detection methods. However, block-based algorithm lacks the ability to resist affine transformation attacks, and interest point-based algorithm is limited to accurately locate the tampered region. To tackle these challenges, a coarse-to-fine model (CFM) is proposed. By extracting features, affine transformation matrix and detecting forgery regions, the localization of tampered areas from sparse to pre

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He, Xiang, Yonghong Song, and Yuanlin Zhang. "A coarse-to-fine scene text detection method based on Skeleton-cut detector and Binary-Tree-Search based rectification." Pattern Recognition Letters 112 (September 2018): 27–33. http://dx.doi.org/10.1016/j.patrec.2018.05.020.

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CLIFT, BEN, and JIM TOMLINSON. "Credible Keynesianism? New Labour Macroeconomic Policy and the Political Economy of Coarse Tuning." British Journal of Political Science 37, no. 1 (2006): 47–69. http://dx.doi.org/10.1017/s0007123407000038.

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This article questions prevailing interpretations of New Labour's political economy and challenges the assumption within the comparative and international political economy literatures of the exhaustion of the Keynesian political economic paradigm. New Labour's doctrinal statements are analysed to establish to what extent these doctrinal positions involve a repudiation of Keynesianism. Although New Labour has explicitly renounced the ‘fine tuning’ often (somewhat problematically) associated with post-war Keynesian political economy, we argue that they have carved out policy space in which to e

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Vivier, Stéphane. "Application of the corrected response surface methodology for the optimization of a permanent magnet synchronous machine." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, no. 2 (2018): 740–54. http://dx.doi.org/10.1108/compel-11-2016-0480.

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PurposeThis paper aims to introduce an original application of the corrected response surface method (CRSM) in the context of the optimal design of a permanent magnet synchronous machine used as an integrated starter generator. This method makes it possible to carry out this design in a very efficient manner, in comparison with conventional optimization approaches. Design/methodology/approachThe search for optimal conditions is achieved by the joint use of two multi-physics models of the machine to be optimized. The former models most finely the physical functioning of the machine; it is calle

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Li, Haichao, Zhi Li, Jianbin Huang, Bo Meng, and Zhimin Zhang. "Accurate hierarchical stereo matching based on 3D plane labeling of superpixel for stereo images from rovers." International Journal of Advanced Robotic Systems 18, no. 2 (2021): 172988142110021. http://dx.doi.org/10.1177/17298814211002113.

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An accurate hierarchical stereo matching method is proposed based on continuous 3D plane labeling of superpixel for rover’s stereo images. This method can infer the 3D plane label of each pixel combined with the slanted-patch matching strategy and coarse-to-fine constraints, which is especially suitable for large-scale scene matching with low-texture or textureless regions. At every level, the stereo matching method based on superpixel segmentation makes the iteration convergence faster and avoids huge redundant computations. In the coarse-to-fine matching scheme, we propose disparity constrai

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Zhang, Xiafen, and Vijayan Sugumaran. "Content Based Search Engine for Historical Calligraphy Images." International Journal of Intelligent Information Technologies 10, no. 3 (2014): 1–18. http://dx.doi.org/10.4018/ijiit.2014070101.

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Paper collections of historical calligraphy objects in Libraries and museums are scanned into document images to serve the academic society. However, these digitized collections are in image format, lacking the technology to search by image content. This paper proposes a search engine for searching calligraphy image content. First, 2503 page images are segmented into characters and components. Second, characters are interactively labeled and features are extracted to build a calligraphy database. When an image search query is submitted, coarse features are first extracted and used to prune the

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Cheng, Fang-Hsuan, and Tze-Yun Sung. "Merging Static and Dynamic Depth Cues with Optical-Flow Recovery for Creating Stereo Videos." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/725301.

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A method for estimating the depth information of a general monocular image sequence and then creating a 3D stereo video is proposed. Distinguishing between foreground and background is possible without additional information, and then foreground pixels are moved to create the binocular image. The proposed depth estimation method is based on coarse-to-fine strategy. By applying the CID method in the spatial domain, the sharpness and the contrast of an image can be improved by the distance of the region based on its color. Then a coarse depth map of the image can be generated. An optical-flow me

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SS, Venkatesh, and Deepak Mishra. "Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations." Journal of Intelligent Systems 30, no. 1 (2020): 142–64. http://dx.doi.org/10.1515/jisys-2019-0233.

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Abstract This paper introduce a new variant of the Genetic Algorithm whichis developed to handle multivariable, multi-objective and very high search space optimization problems like the solving system of non-linear equations. It is an integer coded Genetic Algorithm with conventional cross over and mutation but with Inverse algorithm is varying its search space by varying its digit length on every cycle and it does a fine search followed by a coarse search. And its solution to the optimization problem will converge to precise value over the cycles. Every equation of the system is considered as

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Zhang, Chen, Bin Hu, Yucong Suo, Zhiqiang Zou, and Yimu Ji. "Large-Scale Video Retrieval via Deep Local Convolutional Features." Advances in Multimedia 2020 (June 9, 2020): 1–8. http://dx.doi.org/10.1155/2020/7862894.

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In this paper, we study the challenge of image-to-video retrieval, which uses the query image to search relevant frames from a large collection of videos. A novel framework based on convolutional neural networks (CNNs) is proposed to perform large-scale video retrieval with low storage cost and high search efficiency. Our framework consists of the key-frame extraction algorithm and the feature aggregation strategy. Specifically, the key-frame extraction algorithm takes advantage of the clustering idea so that redundant information is removed in video data and storage cost is greatly reduced. T

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Song, Z. N., and H. G. Sui. "A COARSE-TO-FINE MODEL FOR AIRPLANE DETECTION FROM LARGE REMOTE SENSING IMAGES USING SALIENCY MODLE AND DEEP LEARNING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1571–73. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1571-2018.

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High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieva

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Zhao, Zeng-Shun, Xiang Feng, Sheng-Hua Teng, Yi-Bin Li, and Chang-Shui Zhang. "Multiscale Point Correspondence Using Feature Distribution and Frequency Domain Alignment." Mathematical Problems in Engineering 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/382369.

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In this paper, a hybrid scheme is proposed to find the reliable point-correspondences between two images, which combines the distribution of invariant spatial feature description and frequency domain alignment based on two-stage coarse to fine refinement strategy. Firstly, the source and the target images are both down-sampled by the image pyramid algorithm in a hierarchical multi-scale way. The Fourier-Mellin transform is applied to obtain the transformation parameters at the coarse level between the image pairs; then, the parameters can serve as the initial coarse guess, to guide the followi

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Wang, N., C. M. Tsai, and K. C. Cha. "A Study of Parallel Efficiency of Modified Direct Algorithm Applied to Thermohydrodynamic Lubrication." Journal of Mechanics 25, no. 2 (2009): 143–50. http://dx.doi.org/10.1017/s1727719100002598.

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AbstractThis study examines the parallel computing as a means to minimize the execution time in the optimization applied to thermohydrodynamic (THD) lubrication. The objective of the optimization is to maximize the load capacity of a slider bearing with two design variables. A global optimization method, DIviding RECTangle (DIRECT) algorithm, is used. The first approach was to apply the parallel computing within the THD model in a shared-memory processing (SMP) environment to examine the parallel efficiency of fine-grain computation. Next, a distributed parallel computing in the search level w

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Korah, Reeba, and J. Raja Paul Perinbam. "Fully Pipelined Parallel Architecture for Candidate Block and Pixel-Subsampling-Based Motion Estimation." VLSI Design 2008 (April 20, 2008): 1–8. http://dx.doi.org/10.1155/2008/890410.

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This paper presents a low power and high speed architecture for motion estimation with Candidate Block and Pixel Subsampling (CBPS) Algorithm. Coarse-to-fine search approach is employed to find the motion vector so that the local minima problem is totally eliminated. Pixel subsampling is performed in the selected candidate blocks which significantly reduces computational cost with low quality degradation. The architecture developed is a fully pipelined parallel design with 9 processing elements. Two different methods are deployed to reduce the power consumption, parallel and pipelined implemen

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Deng, Zhongliang, Jun Mo, Buyun Jia, and Xinmei Bian. "A Fine Frequency Estimation Algorithm Based on Fast Orthogonal Search (FOS) for Base Station Positioning Receivers." Electronics 7, no. 12 (2018): 376. http://dx.doi.org/10.3390/electronics7120376.

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Base station signals have been widely studied as a promising navigation and positioning signal. The time and code division-orthogonal frequency division multiplexing (TC-OFDM) signal is a novel communication and navigation fusion signal that can simultaneously implement communication and positioning services. The TC-OFDM signal multiplexes the pseudorandom noise (PRN) code, called positioning code, and the Chinese mobile multimedia broadcasting (CMMB) signal in the same frequency band. For positioning in the TC-OFDM receiver, it is necessary to acquire and track the PRN code phase and the carr

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Jing, Ya, Chenyang Si, Junbo Wang, Wei Wang, Liang Wang, and Tieniu Tan. "Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 11189–96. http://dx.doi.org/10.1609/aaai.v34i07.6777.

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Text-based person search aims to retrieve the corresponding person images in an image database by virtue of a describing sentence about the person, which poses great potential for various applications such as video surveillance. Extracting visual contents corresponding to the human description is the key to this cross-modal matching problem. Moreover, correlated images and descriptions involve different granularities of semantic relevance, which is usually ignored in previous methods. To exploit the multilevel corresponding visual contents, we propose a pose-guided multi-granularity attention

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Sun, Yuantian, Guichen Li, Junfei Zhang, and Deyu Qian. "Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model." Advances in Civil Engineering 2019 (December 28, 2019): 1–7. http://dx.doi.org/10.1155/2019/5198583.

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Rubberized concrete (RC) has attracted more attention these years as it is an economical and environmental-friendly construction material. Normally, the uniaxial compressive strength (UCS) of RC needs to be evaluated before application. In this study, an evolutionary random forest model (BRF) combining random forest (RF) and beetle antennae search (BAS) algorithms was proposed, which can be used for establishing the relationship between UCS of RC and its key variables. A total number of 138 cases were collected from the literature to develop and validate the BRF model. The results showed that

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Qin, Pinle, Jun Chen, Kai Zhang, and Rui Chai. "Convolutional neural networks and hash learning for feature extraction and of fast retrieval of pulmonary nodules." Computer Science and Information Systems 15, no. 3 (2018): 517–31. http://dx.doi.org/10.2298/csis171210020q.

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With a widespread use of digital imaging data in hospitals, the size of medical image repositories is increasing rapidly. This causes difficulty in managing and querying these large databases leading to the need of content based medical image retrieval (CBMIR) systems. A major challenge in CBMIR systems is the ?semantic gap? that exists between the low level visual information captured by imaging devices and high level semantic information perceived by the human. Using deep convolution neural network (CNN) to construct the CBMIR system can fully characterize the high level semantic features in

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CAN, TOLGA, and YUAN-FANG WANG. "PROTEIN STRUCTURE ALIGNMENT AND FAST SIMILARITY SEARCH USING LOCAL SHAPE SIGNATURES." Journal of Bioinformatics and Computational Biology 02, no. 01 (2004): 215–39. http://dx.doi.org/10.1142/s0219720004000533.

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We present a new method for conducting protein structure similarity searches, which improves on the efficiency of some existing techniques. Our method is grounded in the theory of differential geometry on 3D space curve matching. We generate shape signatures for proteins that are invariant, localized, robust, compact, and biologically meaningful. The invariancy of the shape signatures allows us to improve similarity searching efficiency by adopting a hierarchical coarse-to-fine strategy. We index the shape signatures using an efficient hashing-based technique. With the help of this technique w

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Yao, Lewei, Hang Xu, Wei Zhang, Xiaodan Liang, and Zhenguo Li. "SM-NAS: Structural-to-Modular Neural Architecture Search for Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 12661–68. http://dx.doi.org/10.1609/aaai.v34i07.6958.

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The state-of-the-art object detection method is complicated with various modules such as backbone, RPN, feature fusion neck and RCNN head, where each module may have different designs and structures. How to leverage the computational cost and accuracy trade-off for the structural combination as well as the modular selection of multiple modules? Neural architecture search (NAS) has shown great potential in finding an optimal solution. Existing NAS works for object detection only focus on searching better design of a single module such as backbone or feature fusion neck, while neglecting the bal

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Li, Shikun, Ruodan Lu, Jianya Liu, and Liang Guo. "Super Edge 4-Points Congruent Sets-Based Point Cloud Global Registration." Remote Sensing 13, no. 16 (2021): 3210. http://dx.doi.org/10.3390/rs13163210.

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With the acceleration in three-dimensional (3D) high-frame-rate sensing technologies, dense point clouds collected from multiple standpoints pose a great challenge for the accuracy and efficiency of registration. The combination of coarse registration and fine registration has been extensively promoted. Unlike the requirement of small movements between scan pairs in fine registration, coarse registration can match scans with arbitrary initial poses. The state-of-the-art coarse methods, Super 4-Points Congruent Sets algorithm based on the 4-Points Congruent Sets, improves the speed of registrat

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Melais, Saloua, Meriem Fakhreddine Bouali, Ahmed Melaikia, and Amine Amirat. "Effects of coarse sand dosage on the physic-mechanical behavior of sand concrete." Frattura ed Integrità Strutturale 15, no. 56 (2021): 151–59. http://dx.doi.org/10.3221/igf-esis.56.12.

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The development and research of a new formulation of concrete integrating natural resources such as sands (from dunes and/or quarries) as well as waste from steel factories in the form of granulated slag from blast furnaces lead to the development of new sand concretes for which the improvement of specific properties will lead to a search for an agreement between production cost and performance. The objective of this research is to study the influence of the dosage of the size of the largest aggregate on the workability of sand concretes as well as on the compressive strength at 7 days, 14 day

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Hu, Qingxi, Die Feng, Haiguang Zhang, Yuan Yao, Mohamed Aburaia, and Herfried Lammer. "Oriented to Multi-Branched Structure Unsupported 3D Printing Method Research." Materials 13, no. 9 (2020): 2023. http://dx.doi.org/10.3390/ma13092023.

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For the traditional three-axis (3D) configuration of the additive manufacturing (AM) platform, when printing the target model with a multi-branched structure, it is imperative to construct adequate support structures. To eliminate the use of support during the printing process, a non-directional unsupported 3D printing method for five-axis AM is proposed in this paper. By carrying out the K-means clustering algorithm, the coarse partition of the model is obtained, and then the fine decomposition represented by a sequence of separating planes is determined by a local dynamic search adjustment a

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Chapuis, Guillaume, Mathilde Le Boudic-Jamin, Rumen Andonov, Hristo Djidjev, and Dominique Lavenier. "Parallel Seed-Based Approach to Multiple Protein Structure Similarities Detection." Scientific Programming 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/279715.

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Finding similarities between protein structures is a crucial task in molecular biology. Most of the existing tools require proteins to be aligned in order-preserving way and only find single alignments even when multiple similar regions exist. We propose a new seed-based approach that discovers multiple pairs of similar regions. Its computational complexity is polynomial and it comes with a quality guarantee—the returned alignments have both root mean squared deviations (coordinate-based as well as internal-distances based) lower than a given threshold, if such exist. We do not require the ali

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Liu, Yuan, Xiubao Sui, Xiaodong Kuang, Chengwei Liu, Guohua Gu, and Qian Chen. "Object Tracking Based on Vector Convolutional Network and Discriminant Correlation Filters." Sensors 19, no. 8 (2019): 1818. http://dx.doi.org/10.3390/s19081818.

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Due to the fast speed and high efficiency, discriminant correlation filter (DCF) has drawn great attention in online object tracking recently. However, with the improvement of performance, the costs are the increase in parameters and the decline of speed. In this paper, we propose a novel visual tracking algorithm, namely VDCFNet, and combine DCF with a vector convolutional network (VCNN). We replace one traditional convolutional filter with two novel vector convolutional filters in the convolutional stage of our network. This enables our model with few memories (only 59 KB) trained offline to

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