Int. J. Knowl. Eng. Soft Data Paradigms最新文献

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Learning combined features for automatic facial expression recognition 学习面部表情自动识别的组合特征
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-12-02 DOI: 10.1504/ijkesdp.2019.10025583
Nabila Zrira, Mehdi Abouzahir, E. Bouyakhf, Ibtissam Benmiloud, M. M. Himmi
{"title":"Learning combined features for automatic facial expression recognition","authors":"Nabila Zrira, Mehdi Abouzahir, E. Bouyakhf, Ibtissam Benmiloud, M. M. Himmi","doi":"10.1504/ijkesdp.2019.10025583","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.10025583","url":null,"abstract":"Facial expressions are one of the most natural and powerful means for the human being in his social communications, whether to share his internal emotional states or to display his moods or intentions, which, in fact, may be true or simply played in a theatrical way. Given the numerous and variety of applications that can be easily planned, building a system able to automatically recognising facial expressions from images has been an intense field of study in recent years. In this paper, we propose a new framework for automatic facial expression recognition based on combined features and deep learning method. Before the feature extraction, we use Haar feature-based cascade classifier in order to detect then crop the face in the images. Next, we extract pyramid of histogram of gradients (PHOG) as shape descriptors and local binary patterns (LBP) as appearance features to form hybrid feature vectors. Finally, we use those vectors for training deep learning algorithm called deep belief network (DBN). The experimental results on publicly available datasets show promising accuracy in recognising all expression classes, even for experiments which are evaluated on more than seven basic expressions.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127666593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Role-based access control in BagTrac application BagTrac应用中基于角色的访问控制
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-11-29 DOI: 10.1504/ijkesdp.2019.10025586
Kenza Oufaska, M. Boulmalf, K. E. Yassini, Achraf Haibi, Yassir Rouchdi
{"title":"Role-based access control in BagTrac application","authors":"Kenza Oufaska, M. Boulmalf, K. E. Yassini, Achraf Haibi, Yassir Rouchdi","doi":"10.1504/ijkesdp.2019.10025586","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.10025586","url":null,"abstract":"The purpose of this study is to enhance RFID application benefits as a luggage tracking system, first, by defining RFID architecture, components, functioning and middleware roles. Secondly, by discussing the implementation of role-based access control as a tool regulating access to RFID data, therefore making authentication methods more robust and flexible and to eventually presenting our BAG TRAC application, allowing easier manipulation and real-time visualisation of the luggage transportation process.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129695114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fuzzy detection orange tree leaves diseases using a co-occurrence matrix-based K-nearest neighbours classifiers 基于共现矩阵的k近邻分类器模糊检测橘子树叶片病害
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-11-29 DOI: 10.1504/ijkesdp.2019.10025585
F. Jakjoud, A. Hatim, Abella Bouaddi
{"title":"Fuzzy detection orange tree leaves diseases using a co-occurrence matrix-based K-nearest neighbours classifiers","authors":"F. Jakjoud, A. Hatim, Abella Bouaddi","doi":"10.1504/ijkesdp.2019.10025585","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.10025585","url":null,"abstract":"The improvement of production efficiency in the farming environment is nowadays of a great interest in the agriculture industry. Several techniques and technologies are used to overcome the main problems facing the developments on this field. In this paper, the farms image processing-based automatic monitoring is treated. We propose an image processing approach for lemon tree leaves diseases. Our approach is a combination of a fuzzy decision maker and KNN classifiers based on Haralick parameters extracted from the co-occurrence matrix. The testing results are very satisfactory and the efficiency of our system could reach aver than 90% for a limited database.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134252062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Visual content summarisation for instructional videos using AdaBoost and SIFT 使用AdaBoost和SIFT对教学视频进行视觉内容总结
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-11-29 DOI: 10.1504/ijkesdp.2019.10025587
Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour
{"title":"Visual content summarisation for instructional videos using AdaBoost and SIFT","authors":"Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour","doi":"10.1504/ijkesdp.2019.10025587","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.10025587","url":null,"abstract":"Research contributions in video retrieval field are rising to propose solutions for automatic understanding and retrieval of video content. The aim is to make the user able to retrieve specific video sequences in a large database, based on semantic information. In this paper, we process a special case of videos, instructional videos, where text presents very rich semantic information for understanding video content. Indeed, lecture videos are the source of information used in learning systems by educators and students for archiving and sharing knowledge. However, users usually have difficulties to access accurate parts in instructional videos. In our paper, we propose a method to summarise the visual content in instructional videos. For that, first, we segment the video into shots based on SIFT. Then, key frames which are rich in text and figures are extracted from each shot based on entropy measurement. These keyframes are classified using AdaBoost to eliminate non-text frames. The text content in the lecture video summary can be detected and recognised to identify keywords for indexing and classification.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123992317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An efficient similarity search using a combination between descriptors: a case of study in human face recognition 基于描述符组合的高效相似性搜索:人脸识别案例研究
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-11-29 DOI: 10.1504/ijkesdp.2019.10025584
Nawfal El Maliki, H. Silkan, M. E. Maghri
{"title":"An efficient similarity search using a combination between descriptors: a case of study in human face recognition","authors":"Nawfal El Maliki, H. Silkan, M. E. Maghri","doi":"10.1504/ijkesdp.2019.10025584","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.10025584","url":null,"abstract":"Face recognition is one of the important fields of search in computer vision. Its principle consists to look for images that represent the similar faces to a given face image the image request. This process is done by extracting a set of features of the request image then making comparison between features generated by the request one and the others extracted from whole face image database. Recently, numerous face representation and classification methods have been proposed in the literature. Nevertheless, many issues related to indexing, combination of adequate descriptors and time computing have not yet been solved. In this paper, we deal with problems related to features combination and this, by conceiving a preformat content-based image retrieval that is mainly oriented to handle face authentication challenges. Its convivial interface allows to user the selection of appropriate weighting coefficient values associate to each feature based on human judgment in order to enhance the retrieval performance. We have tested our proposed method on ORL database by using a set of known features. The obtained results show the performance of our proposed method.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123869288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Estimation of the threshold parameter of a wear-out failure period in the case of a three-parameter Weibull distribution 三参数威布尔分布下磨损失效期阈值参数的估计
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-10-04 DOI: 10.1504/ijkesdp.2019.102818
Takatoshi Sugiyama, T. Ogura, T. Sugiyama
{"title":"Estimation of the threshold parameter of a wear-out failure period in the case of a three-parameter Weibull distribution","authors":"Takatoshi Sugiyama, T. Ogura, T. Sugiyama","doi":"10.1504/ijkesdp.2019.102818","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.102818","url":null,"abstract":"We aimed to estimate the threshold parameter for the wear-out failure period of a three-parameter Weibull distribution. In this paper, we propose the minimum-variance linear unbiased estimator based on order statistics, which is denoted by 'TBEST'. In Section 2, we verify the validity of TBEST by comparing it with the existing threshold parameter estimator, based on simulation studies of bias and mean squared error (MSE). Our results show that TBEST requires all order statistics, except for the case of an exponential distribution, in which TBEST is reduced to an unbiased estimator based on the smallest observation only. In Section 3, by simulation studies, we compare TBEST and other estimators known to have good performances. In the simulation results, bias and MSE of TBEST were the smallest in most cases. We also show a numerical example to measure fatigue lives in hours of ten bearings from McCool (1974).","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114447078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Hybrid key management scheme for heterogeneous wireless sensor networks 异构无线传感器网络的混合密钥管理方案
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-10-03 DOI: 10.1504/IJKESDP.2019.10020639
R. Sharmila, V. Vijayalakshmi
{"title":"Hybrid key management scheme for heterogeneous wireless sensor networks","authors":"R. Sharmila, V. Vijayalakshmi","doi":"10.1504/IJKESDP.2019.10020639","DOIUrl":"https://doi.org/10.1504/IJKESDP.2019.10020639","url":null,"abstract":"Wireless sensor network (WSN) is a large scale network with thousands of tiny sensor nodes deployed in the field which is widely used in real time applications. The greatest issue in wireless sensor network is secure key establishment and communication. In this paper, hybrid key management scheme is proposed for heterogeneous WSN. Initially the keys are generated and pre-distributed into sensor nodes using hyper elliptic curve equation. After the deployment, the node tries to form a cluster and then establishes a symmetric key using orthogonal Latin square method, where the cluster heads and base station use public key encryption method based on hyper elliptic curve cryptography (HECC). The simulation results show that the proposed scheme is better in terms of robustness, connectivity and lesser computational overhead with reduced key size.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115697489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An optimal dimension reduction-based feature selection and classification strategy for geospatial imagery 基于降维的地理空间图像特征选择与分类策略
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-10-03 DOI: 10.1504/ijkesdp.2019.102851
Ajeet Singh, Vikas Tiwari
{"title":"An optimal dimension reduction-based feature selection and classification strategy for geospatial imagery","authors":"Ajeet Singh, Vikas Tiwari","doi":"10.1504/ijkesdp.2019.102851","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.102851","url":null,"abstract":"Driven by the explosive growth on the available data nowadays and advancement of technologies, the strong need arises for utilising and maintaining the available data. However, while building an expert prediction system, the inconsistency present in the information system, incompleteness of available knowledge base, continuous natured attribute values and noise present in the system (especially in case of spatial image data handling), are prime factors which may degrade the process of classification with available traditional methods. Our proposed construction adopts an efficient strategy for classification. Here we explore the problem of classifying remote sensing satellite images. Image data pre-processing and its categorisation refers to the labelling of individual pixel object instances into one of a number of predefined categories. Although this is usually not a much intractable task for humans, it has proved to be an extremely difficult problem for machines. We performed experimental analysis for classification using NWPU-RESISC45 dataset. Experiment result shows the improvement in classification by adopting our proposed strategy over other significant state of the art.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123944629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Image data hiding scheme based on spline interpolation and OPAP 基于样条插值和OPAP的图像数据隐藏方案
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2019-10-03 DOI: 10.1504/ijkesdp.2019.102880
Amine Benhfid, El Bachir Ameur
{"title":"Image data hiding scheme based on spline interpolation and OPAP","authors":"Amine Benhfid, El Bachir Ameur","doi":"10.1504/ijkesdp.2019.102880","DOIUrl":"https://doi.org/10.1504/ijkesdp.2019.102880","url":null,"abstract":"In this paper we propose an image steganography method based on the spline interpolation. Firstly, digital images are often transmitted over the Internet which would arouse little suspicion. Secondly, the high correlation between pixels provides rich space for data embedding; in addition, optimal pixel adjustment procedure (OPAP) is employed to minimise the error between the input image and the output image in order to ameliorate the fidelity of the proposed steganography method. We propose image steganography methods in spatial domain by using a nearest neighbour, bilinear and bicubic spline interpolation technique, which can embed a large amount of secret data into images with imperceptible modification. The interpolation error, which is measured by distance between the maximum value and the predicted value, is used to embed the secret data. The experimental results show that the proposed schemes provide a larger payload and a good image quality.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123779999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identifying behaviour objective from traffic behaviour log data by using facility ontology 利用设施本体从交通行为日志数据中识别行为目标
Int. J. Knowl. Eng. Soft Data Paradigms Pub Date : 2016-04-01 DOI: 10.1504/IJKESDP.2016.075975
Yu Sugawara, Takeshi Morita, H. Abe, Shuichi Matsumoto, Takahira Yamaguchi
{"title":"Identifying behaviour objective from traffic behaviour log data by using facility ontology","authors":"Yu Sugawara, Takeshi Morita, H. Abe, Shuichi Matsumoto, Takahira Yamaguchi","doi":"10.1504/IJKESDP.2016.075975","DOIUrl":"https://doi.org/10.1504/IJKESDP.2016.075975","url":null,"abstract":"Traffic behaviour surveys by hand require both a lot of money and human resources. Recently, traffic behaviour surveys using information technology have been carried out. In this study, we propose a method to extract staying points from GPS-based positional data, to identify the types of staying facilities by using Google Places API, a facility ontology, the regularity which is analysed from trip chains about traffic behaviour and to determine the behaviour objectives based on the rules between the behaviour objectives and the types of staying facilities. This method could identify 67.9% behaviour objectives in the evaluation using GPS location data from the traffic behaviour survey in Nagasaki.","PeriodicalId":347123,"journal":{"name":"Int. J. Knowl. Eng. Soft Data Paradigms","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116829540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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