• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.120-124
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• 2021

Recently, human attribute recognition (HAR) attracts a lot of attention due to its wide application in video surveillance systems. Recent deep-learning-based solutions for HAR require time-consuming training processes. In this paper, we propose a post-processing technique that utilizes the historical video frames to improve prediction results without invoking re-training or modifying existing deep-learning-based classifiers. Experiment results on a large-scale benchmark dataset show the effectiveness of our proposed method.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.128-132
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• 2023

Recently, with the development of deep learning technology, research on pedestrian attribute recognition technology using deep neural networks has been actively conducted. Existing pedestrian attribute recognition techniques can be obtained in such a way as global-based, regional-area-based, visual attention-based, sequential prediction-based, and newly designed loss function-based, depending on how pedestrian attributes are detected. It is known that the performance of these pedestrian attribute recognition technologies varies greatly depending on the type of backbone network that constitutes the deep neural networks model. Therefore, in this paper, several backbone networks are applied to the baseline pedestrian attribute recognition model and the performance changes of the model are analyzed. In this paper, the analysis is conducted using Resnet34, Resnet50, Resnet101, Swin-tiny, and Swinv2-tiny, which are representative backbone networks used in the fields of image classification, object detection, etc. Furthermore, this paper analyzes the change in time complexity when inferencing each backbone network using a CPU and a GPU.

• Journal of Biomedical Engineering Research
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• v.12 no.2
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• pp.121-130
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• 1991

This paper presents a QRS recognition algorithm using attribute grammar and its interpreter. This system extracts primitive and their attributes by linear approximation technique and then represented linguistic formation using attribute grammar. These nonterminals and their attributes are evaluated by attribute grammar interpreter. The performance of the QRS recognition algorithm has been evaluated using arrhythmia simulator and CSE ECG library.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.39-45
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• 2018

Purpose - The purpose of this study is to examine the image similarity and attribute recognition of the top 10 rated spa destinations (Chungnam Deoksan, Chungnam Dogo, Busan Dongrae, Daejeon Yuseong, Chungnam Asan, Gyeongbuk Bomun, Chungbuk Suanbo, Gyeongnam Jangyu, Chungnam Onyang, & Gyeongbol Bugok) in Korea based on the visits to these spa places by the customers. Research design, data, and methodology - The survey of this study was conducted on the visitors to the top 10 spa destinations in Korea from April 8 ~ April 21, 2017, and a total of 300 questionnaires were distributed. Of them, effective questionnaires used in the final study were a total of 241. In this study, empirical analysis was made through frequency analysis, factor analysis, and multidimensional scaling ALSCAL(spinning symmetry for image similarity and rectangle for attributes recognition) by using the Statistics Package SPSS 24.0. Results - According to the analysis result of spa destination image similarity, the stress level was 0.16453 and the level of the stress was good. Moreover, the coefficient of determination (RSQ) was, which had a description of each aspect of the spa destination, 0.79908. According to the results of attribute recognition, the stress value of 0.11805 represents a degree of conformity, and the coefficient of determination(RSQ) appeared at 0.98665. Therefore, the results of this analysis are that the similarities between spa destinations and the attribute recognition of the spa destinations is a suitable model that is properly expressed in two dimensions. Conclusions - First, according to the analysis result of image similarity, Deoksan & Dogo spa revealed similar images, as well as the Dongrae and Yuseong spa, while on the contrary Asan, Bomun, Suanbo spa has different images from the rest. Second, according to the results of attribute recognition, Asan and Onyang spa has competitiveness in terms of accessibility to spa destination; Yuseong, Dongrae, Jangyu spa in terms of spa facilities, spa tourism conditions, and service & shopping conditions. while spa water quality and spa costs showed low attribute reflection for all 10 spas. Therefore, the spa visitors cannot recognize the differentiation of spa water quality and spa costs.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1031-1033
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• 2005

This paper presents a system of handwritten numerals recognition, which is based on Ant-miner algorithm (data mining based on Ant colony optimization). At the beginning, three distinct fractures (also called attributes) of each numeral are extracted. The attributes are Loop zones, End points, and Feature codes. After these data are extracted, the attributes are in the form of attribute = value (eg. End point10 = true). The extraction is started by dividing the numeral into 12 zones. The numbers 1-12 are referenced for each zone. The possible values of Loop zone attribute in each zone are "true" and "false". The meaning of "true" is that the zone contains the loop of the numeral. The Endpoint attribute being "true" means that this zone contains the end point of the numeral. There are 24 attributes now. The Feature code attribute tells us how many lines of a numeral are passed by the referenced line. There are 7 referenced lines used in this experiment. The total attributes are 31. All attributes are used for construction of the classification rules by the Ant-miner algorithm in order to classify 10 numerals. The Ant-miner algorithm is adapted with a little change in this experiment for a better recognition rate. The results showed the system can recognize all of the training set (a thousand items of data from 50 people). When the unseen data is tested from 10 people, the recognition rate is 98 %.

• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.67-78
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• 2018

The stability of cutting slope influences the safety of railway operation, and how to identify the stability of the slope quickly and determine the rational monitoring plan is a pressing problem at present. In this study, the attribute recognition model of risk assessment for high cutting slope stability in the heavy haul railway is established based on attribute mathematics theory, followed by the consequent monitoring scheme design. Firstly, based on comprehensive analysis on the risk factors of heavy haul railway loess slope, collapsibility, tectonic feature, slope shape, rainfall, vegetation conditions, train speed are selected as the indexes of the risk assessment, and the grading criteria of each index is established. Meanwhile, the weights of the assessment indexes are determined by AHP judgment matrix. Secondly, The attribute measurement functions are given to compute attribute measurement of single index and synthetic attribute, and the attribute recognition model was used to assess the risk of a typical heavy haul railway loess slope, Finally, according to the risk assessment results, the monitoring content and method of this loess slope were determined to avoid geological disasters and ensure the security of the railway infrastructure. This attribute identification- risk assessment- monitoring design mode could provide an effective way for the risk assessment and control of heavy haul railway in the loess plateau.

• Journal of the Korean association of regional geographers
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• v.11 no.4
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• pp.497-510
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• 2005

The purpose of this study was to examine the image similarity, preference, and the attribute recognition using multidimensional scaling. The analyses were carried out by 5 spa destinations located in Choongchung area. The results were as followings: first, considering the image similarity, the image of Suanbo & Onyang and Dogo & Asan were similar except for the Yusung. Second, considering the attribute recognition, Yusung had a stronger attribute reflecting spa tradition when compared to other competitive spa destinations. Onyang showed a strong attribute of facilities. Dogo had a stronger point about use cost. Suanbo had relatively strong attributes in terms of facilities, customer service, and accessability. However, the water quality of spa destination and activities were not reflected in attribute recognition because these two attributes was farthest from the spa destination. Third, considering the preference of selecting spa destinations, package tourists had a strong preference about Yusung, individual tourists, family, incentive tourists prefer Suanbo, followed by Dogo and Yusung. Group tourists had a strong preference about Dogo.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6133-6151
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• 2017

The field of periocular biometrics has gained wide attention as an alternative or supplemental means to conventional biometric traits such as the iris or the face. Periocular biometrics provide intermediate resolution between the iris and the face, which enables it to support both. We have developed a periocular recognition system by using uniform Multiscale Local Binary Pattern (uMLBP) and attribute features. The proposed system has been evaluated in terms of major factors that need to be considered on a mobile platform (e.g., distance and facial pose) to assess the feasibility of the use of periocular biometrics on mobile devices. Experimental results showed 98.7% of rank-1 identification accuracy on a subset of the Face Recognition Grand Challenge (FRGC) database, which is the best performance among similar studies.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.56-60
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• 1991

This paper describes an algorithm that recognizing the QRS complex using attribute grammar interpreter. This System extracts primitives and their attributes by linear approximation and then evaluated by attribute grammar interpreter.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2935-2937
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• 1999

The human has recognizable part of body such as a fingerprint, a crimson, a blood vessel. This part has been investigated constantly, its confidence for personal recognition is high. In spite of specialized part of human body, a lip print recognition is developed less than the other physical attribute that is a fingerprint. a voice pattern, a retinal blood-vessel pattern, or a facial recognition. This paper is to implement hardware for lip print recognition system using VHDL.