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Article
Publication date: 14 August 2017

Ning Xian

The purpose of this paper is to propose a new algorithm chaotic pigeon-inspired optimization (CPIO), which can effectively improve the computing efficiency of the basic…

Abstract

Purpose

The purpose of this paper is to propose a new algorithm chaotic pigeon-inspired optimization (CPIO), which can effectively improve the computing efficiency of the basic Itti’s model for saliency-based detection. The CPIO algorithm and relevant applications are aimed at air surveillance for target detection.

Design/methodology/approach

To compare the improvements of the performance on Itti’s model, three bio-inspired algorithms including particle swarm optimization (PSO), brain storm optimization (BSO) and CPIO are applied to optimize the weight coefficients of each feature map in the saliency computation.

Findings

According to the experimental results in optimized Itti’s model, CPIO outperforms PSO in terms of computing efficiency and is superior to BSO in terms of searching ability. Therefore, CPIO provides the best overall properties among the three algorithms.

Practical implications

The algorithm proposed in this paper can be extensively applied for fast, accurate and multi-target detections in aerial images.

Originality/value

CPIO algorithm is originally proposed, which is very promising in solving complicated optimization problems.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 1 August 2016

Chunlei Li, Ruimin Yang, Zhoufeng Liu, Guangshuai Gao and Qiuli Liu

Fabric defect detection plays an important role in textile quality control. The purpose of this paper is to propose a fabric defect detection algorithm using learned…

Abstract

Purpose

Fabric defect detection plays an important role in textile quality control. The purpose of this paper is to propose a fabric defect detection algorithm using learned dictionary-based visual saliency.

Design/methodology/approach

First, the test fabric image is splitted into image blocks, and the learned dictionary with normal samples and defective sample is constructed by selecting the image block local binary pattern features with highest or lowest similarity comparing with the average feature vector; second, the first L largest correlation coefficients between each test image block and the dictionary are calculated, and other correlation coefficients are set to zeros; third, the sum of the non-zeros coefficients corresponding to defective samples is used to generate saliency map; finally, an improve valley-emphasis method can efficiently segment the defect region.

Findings

Experimental results demonstrate that the generated saliency map by the proposed method can efficiently outstand defect region comparing with the state-of-the-art, and segment results can precisely localize defect region.

Originality/value

In this paper, a novel fabric defect detection scheme is proposed via learned dictionary-based visual saliency.

Details

International Journal of Clothing Science and Technology, vol. 28 no. 4
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 26 August 2014

Xing Wang, Zhenfeng Shao, Xiran Zhou and Jun Liu

This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and…

Abstract

Purpose

This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images.

Design/methodology/approach

A novel remote sensing image retrieval method based on VSP (visual salient point) features is proposed in this paper. A key point detector and descriptor are used to extract the critical features and their descriptors in remote sensing images. A visual attention model is adopted to calculate the saliency map of the images, separating the salient regions from the background in the images. The key points in the salient regions are then extracted and defined as VSPs. The VSP features can then be constructed. The similarity between images is measured using the VSP features.

Findings

According to the experiment results, compared with traditional visual features, VSP features are more precise and stable in representing diverse remote sensing images. The proposed method performs better than the traditional methods in image retrieval precision.

Originality/value

This paper presents a novel remote sensing image retrieval method based on VSP features.

Details

Sensor Review, vol. 34 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 15 May 2017

Dong Liu, Ming Cong, Yu Du, Qiang Zou and Yingxue Cui

This paper aims to focus on the autonomous behavior selection issue of robotics from the perspective of episodic memory in cognitive neuroscience with biology-inspired…

Abstract

Purpose

This paper aims to focus on the autonomous behavior selection issue of robotics from the perspective of episodic memory in cognitive neuroscience with biology-inspired attention system. It instructs a robot to follow a sequence of behaviors. This is similar to human travel to a target location by guidance.

Design/methodology/approach

The episodic memory-driving Markov decision process is proposed to simulate the organization of episodic memory by introducing neuron stimulation mechanism. Based on the learned episodic memory, the robotic global planning method is proposed for efficient behaviors sequence prediction using bottom-up attention. Local behavior planning based on risk function and feasible paths is used for behavior reasoning under imperfect memory. Aiming at the problem of whole target selection under redundant environmental information, a top-down attention servo control method is proposed to effectively detect the target containing multi-parts and distractors which share same features with the target.

Findings

Based on the proposed method, the robot is able to accumulate experience through memory, and achieve adaptive behavior planning, prediction and reasoning between tasks, environment and threats. Experimental results show that the method can balance the task objectives, select the suitable behavior according to current environment.

Originality/value

The behavior selection method is integrated with cognitive levels to generate optimal behavioral sequence. The challenges in robotic planning under uncertainty and the issue of target selection under redundant environment are addressed.

Details

Industrial Robot: An International Journal, vol. 44 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

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Book part
Publication date: 28 September 2020

Matthew Willcox

Abstract

Details

The Business of Choice: How Human Instinct Influences Everyone’s Decisions
Type: Book
ISBN: 978-1-83982-071-7

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Article
Publication date: 15 April 2020

Xiaoliang Qian, Jing Li, Jianwei Zhang, Wenhao Zhang, Weichao Yue, Qing-E Wu, Huanlong Zhang, Yuanyuan Wu and Wei Wang

An effective machine vision-based method for micro-crack detection of solar cell can economically improve the qualified rate of solar cells. However, how to extract…

Abstract

Purpose

An effective machine vision-based method for micro-crack detection of solar cell can economically improve the qualified rate of solar cells. However, how to extract features which have strong generalization and data representation ability at the same time is still an open problem for machine vision-based methods.

Design/methodology/approach

A micro-crack detection method based on adaptive deep features and visual saliency is proposed in this paper. The proposed method can adaptively extract deep features from the input image without any supervised training. Furthermore, considering the fact that micro-cracks can obviously attract visual attention when people look at the solar cell’s surface, the visual saliency is also introduced for the micro-crack detection.

Findings

Comprehensive evaluations are implemented on two existing data sets, where subjective experimental results show that most of the micro-cracks can be detected, and the objective experimental results show that the method proposed in this study has better performance in detecting precision.

Originality/value

First, an adaptive deep features extraction scheme without any supervised training is proposed for micro-crack detection. Second, the visual saliency is introduced for micro-crack detection.

Details

Sensor Review, vol. 40 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 19 September 2019

Gayatri Nayak and Mitrabinda Ray

Test suite prioritization technique is the process of modifying the order in which tests run to meet certain objectives. Early fault detection and maximum coverage of…

Abstract

Purpose

Test suite prioritization technique is the process of modifying the order in which tests run to meet certain objectives. Early fault detection and maximum coverage of source code are the main objectives of testing. There are several test suite prioritization approaches that have been proposed at the maintenance phase of software development life cycle. A few works are done on prioritizing test suites that satisfy modified condition decision coverage (MC/DC) criteria which are derived for safety-critical systems. The authors know that it is mandatory to do MC/DC testing for Level A type software according to RTCA/DO178C standards. The paper aims to discuss this issue.

Design/methodology/approach

This paper provides a novel method to prioritize the test suites for a system that includes MC/DC criteria along with other important criteria that ensure adequate testing.

Findings

In this approach, the authors generate test suites from the input Java program using concolic testing. These test suites are utilized to measure MC/DC% by using the coverage calculator algorithm. Now, use MC/DC% and the execution time of these test suites in the basic particle swarm optimization technique with a modified objective function to prioritize the generated test suites.

Originality/value

The proposed approach maximizes MC/DC% and minimizes the execution time of the test suites. The effectiveness of this approach is validated by experiments on 20 moderate-sized Java programs using average percentage of fault detected metric.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 1 June 2000

K. Wiak

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction…

Abstract

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 19 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 1 January 2012

Luigi Alberti, Nicola Bianchi and Samad Taghipour Boroujeni

To purpose of this paper is to introduce a procedure to compute the d‐ and q‐axis parameters of the induction motor.

Abstract

Purpose

To purpose of this paper is to introduce a procedure to compute the d‐ and q‐axis parameters of the induction motor.

Design/methodology/approach

A finite element procedure, based on the d‐ and q‐axis model of the induction motor is adopted.

Findings

Such a procedure is well suited to analyse IM with anisotropic rotor, where an intentionally created saliency is introduced in the rotor bar geometry, so as to detect the IM rotor position without sensor.

Originality/value

The proposed procedure allows one to evaluate the sensorless control capability of the IM. It will be useful for both analysis of the IM performance and design of the machine itself.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 31 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 5 September 2016

Murat Caner, Chris Gerada, Greg Asher and Tolga Özer

The purpose of this paper is to investigate Halbach array effects in surface mounted permanent magnet machine (SMPM) in terms of both self-sensing and torque capabilities…

Abstract

Purpose

The purpose of this paper is to investigate Halbach array effects in surface mounted permanent magnet machine (SMPM) in terms of both self-sensing and torque capabilities. A comparison between a conventional SMPM, which has radially magnetized rotor, and a Halbach machine has been carried out.

Design/methodology/approach

The geometric parameters of the two machines have been optimized using genetic algorithm (GA) with looking Pareto. The performance of the machines’ geometry has been calculated by finite element analysis (FEA) software, and two parametric machine models have been realized in Matlab coupled with the FEA and GA toolboxes. Outer volume of the machine, thus copper loss per volume has been kept constant. The Pareto front approach, which simultaneously considers looks two aims, has been used to provide the trade-off between the torque and sensorless performances.

Findings

The two machines’ results have been compared separately for each loading condition. According to the results, the superiority of the Halbach machine has been shown in terms of sensorless capability compromising torque performance. Additionally, this paper shows that the self-sensing properties of a SMPM machine should be considered at the design stage of the machine.

Originality/value

A Halbach machine design optimization has been presented using Pareto optimal set which provides a trade-off comparison between two aims without using weightings. These are sensorless performance and torque capability. There is no such a work about sensorless capability of the Halbach type SMPM in the literature.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 35 no. 5
Type: Research Article
ISSN: 0332-1649

Keywords

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