• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.819-833
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• 2013

Computing global features based on local features using a bio-inspired framework has shown promising performance. However, for some tough applications with large intra-class variances, a single local feature is inadequate to represent all the attributes of the images. To integrate the complementary abilities of multiple local features, in this paper we have extended the efficacy of the bio-inspired framework, HMAX, to adapt heterogeneous features for global feature extraction. Given multiple global features, we propose an approach, designated as parameterized metric learning, for high dimensional feature fusion. The fusion parameters are solved by maximizing the canonical correlation with respect to the parameters. Experimental results show that our method achieves significant improvements over the benchmark bio-inspired framework, HMAX, and other related methods on the Caltech dataset, under varying numbers of training samples and feature elements.

• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• Earthquakes and Structures
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• v.9 no.5
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• pp.957-981
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• 2015

Earthquakes occur as a cluster in many regions around the world where complex fault systems exist. The repeated shaking usually induces accumulative damage to affected structures. Damage accumulation in structural systems increases their level of degradation in stiffness and also reduces their strength. Many existing analytical tools of modeling RC structures lack the salient damage features that account for stiffness and strength degradation resulting from repeated earthquake loading. Therefore, these tools are inadequate to study the response of structures in regions prone to multiple earthquakes hazard. The objective of this paper is twofold: (a) develop a tool that contains appropriate damage features for the numerical analysis of RC structures subjected to more than one earthquake; and (b) conduct a parametric study that investigates the effects of multiple earthquakes on the response of RC moment resisting frame systems. For this purpose, macroscopic constitutive models of concrete and steel materials that contain the aforementioned damage features and are capable of accurately capturing materials degrading behavior, are selected and implemented into fiber-based finite element software. Furthermore, finite element models that utilize the implemented concrete and steel stress-strain hysteresis are developed. The models are then subjected to selected sets of earthquake sequences. The results presented in this study clearly indicate that the response of degrading structural systems is appreciably influenced by strong-motion sequences in a manner that cannot be predicted from simple analysis. It also confirms that the effects of multiple earthquakes on earthquake safety can be very considerable.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.4-100
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• 2002

For visual navigation, mobile robot can use a stereo camera which has large field of view. In this paper, we propose an algorithm to detect and recognize human face on the basis of such camera system. In this paper, a new coarse to fine detection algorithm is proposed. For coarse detection, nearly face-like areas are found in entire image using dual ellipse templates. And, detailed alignment of facial outline and features is performed on the basis of view- based multiple appearance model. Because it hard to finely align with facial features in this case, we try to find most resembled face image area is selected from multiple face appearances using most distinguished facial features- two eye...

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.335-343
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• 2002

A segment matching algorithm in stereo vision via the fusion of multiple features on long edge segments is proposed. One problem of the previous segment matching algorithm is the similarity among the segments caused from its short length. In the proposed algorithm, edges are composed of longer segments which are obtained by breaking the edges only at the locations with distinguished changes of the shape. Such long segments can contain extra features such as curvature ratio and length of segments which could not be included in shorter ones. Use of such additional features enhances the matching accuracy significantly To fuse multiple features for matching, weighting value determination algorithm which is computed according to the degree of the contribution of each factor is proposed. The stereo matching simulations with the proposed algorithm are done about various images and their results are included.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.502-510
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• 2016

Considering video copy transform diversity, a multi-feature video copy detection algorithm based on a Speeded-Up Robust Features (SURF) local descriptor is proposed in this paper. Video copy coarse detection is done by an ordinal measure (OM) algorithm after the video is preprocessed. If the matching result is greater than the specified threshold, the video copy fine detection is done based on a SURF descriptor and a box filter is used to extract integral video. In order to improve video copy detection speed, the Hessian matrix trace of the SURF descriptor is used to pre-match, and dimension reduction is done to the traditional SURF feature vector for video matching. Our experimental results indicate that video copy detection precision and recall are greatly improved compared with traditional algorithms, and that our proposed multiple features algorithm has good robustness and discrimination accuracy, as it demonstrated that video detection speed was also improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2154-2168
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• 2022

Our work addresses the issues associated with usage of the semantic features by Bag of Words model, which requires construction of the dictionary. Extracting the relevant features and clustering them into code book or dictionary is computationally intensive and requires large storage area. Hence we propose to use a simple distribution of multiple shape based features, which is a mixture of gradients, radius and slope angles requiring very less computational cost and storage requirements but can serve as an equivalent image representative. The experimental work conducted on PASCAL VOC 2007 dataset exhibits marginally closer performance in terms of accuracy with the Bag of Word model using Self Organizing Map for clustering and very significant computational gain.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.197-203
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• 2018

Long Term Evolution-Advanced (LTE-A) is the next drive in the broadband mobile communication, which allows operators to improve networks performance and service capabilities. LTE-A targets the peak data rates of 1Gbps in the downlink and 500Mbps in the uplink. This requirement is only fulfilled by a transmission bandwidth of up to 100MHz. However the accessibility of such large part of the contiguous spectrum is uncommon in practice. Therefore LTE-A uses some new features on top of the existing LTE standards to provide very high data rate transmission. Some of the most significant features introduced in LTE-A are carrier aggregation, heterogeneous network enhancement, coordinated multipoint transmission and reception, enhanced multiple input and multiple output, and development relay nodes with universal frequency reuse. This review paper presents an overview of the above mentioned LTE-A key features and functionalities. Based on this review, in the conclusion we discuss the current technical challenges for future broadband mobile communication systems.

• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2095-2103
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• 2004

A macro-level CAPP system is proposed to plan the complicated mechanical prismatic parts efficiently. The system creates the efficient machining sequence of the features in a part by analyzing the feature information. Because the planning with the individual features is very complicated, feature groups are formed for effective planning using the nested relations of the features of a part, and special feature groups are determined for sequencing. The process plan is generated based on the sequences of the feature groups and features. When multiple machines are required, efficient machine assignment is performed. A series of heuristic rules are developed to accomplish it.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.493-496
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.