• ETRI Journal
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• v.38 no.2
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• pp.347-355
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• 2016

In face examinations, gender classification (GC) is one of several fundamental tasks. Recent literature on GC primarily utilizes datasets containing high-resolution images of faces captured in uncontrolled real-world settings. In contrast, there have been few efforts that focus on utilizing low-resolution images of faces in GC. We propose a GC method based on a pixel classifier boosting with modified census transform features. Experiments are conducted using large datasets, such as Labeled Faces in the Wild and The Images of Groups, and standard protocols of GC communities. Experimental results show that, despite using low-resolution facial images that have a 15-pixel inter-ocular distance, the proposed method records a higher classification rate compared to current state-of-the-art GC algorithms.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.252-255
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• 2008

In this paper, we apply a discriminative weight training to a support vector machine (SVM) based gender identification. In our approach, the gender decision rule is expressed as the SVM of optimally weighted mel-frequency cepstral coefficients (MFCC) based on a minimum classification error (MCE) method which is different from the previous works in that different weights are assigned to each MFCC filter bank which is considered more realistic. According to the experimental results, the proposed approach is found to be effective for gender identification using SVM.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.113-118
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• 2011

In this paper, we develop a speaker gender classification technique using collaborative sensor fusion for use in a wireless sensor network. The distributed sensor nodes remove the unwanted input data using the BER(Band Energy Ration) based voice activity detection, process only the relevant data, and transmit the hard labeled decisions to the fusion center where a global decision fusion is carried out. This takes advantages of power consumption and network resource management. The Bayesian sensor fusion and the global weighting decision fusion methods are proposed to achieve the gender classification. As the number of the sensor nodes varies, the Bayesian sensor fusion yields the best classification accuracy using the optimal operating points of the ROC(Receiver Operating Characteristic) curves_ For the weights used in the global decision fusion, the BER and MCL(Mutual Confidence Level) are employed to effectively combined at the fusion center. The simulation results show that as the number of the sensor nodes increases, the classification accuracy was even more improved in the low SNR(Signal to Noise Ration) condition.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1035-1045
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• 2017

Classification of age and gender has been carried out through different approaches such as facial-based and audio-based classifications. One of the limitations of facial-based methods is the reduced recognition rate over large distances, while another is the prerequisite of the faces to be located in front of the camera. Similarly, in audio-based methods, the recognition rate is reduced in a noisy environment. In contrast, gait-based methods are only required that a target person is in the camera. In previous works, the view point of a camera is only available as a side view and gait data sets consist of a standard gait, which is different from an ordinary gait in a real environment. We propose a feature extraction method using skeleton models from an RGB-D sensor by considering characteristics of age and gender using ordinary gait. Experimental results show that the proposed method could efficiently classify age and gender within a target group of individuals in real-life environments.

• Phonetics and Speech Sciences
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• v.1 no.2
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• pp.163-171
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• 2009

This study attempted to investigate vocal characteristics and differences in gender and voice classification among classical singers. Twenty-three female singers (M = 23.1 yrs, SD = 3.6 yrs, average 6.3 yrs singing experience, all classified as sopranos) and twenty male singers (M = 25.2 yrs, SD= 3.6 yrs, average 6. 3 yrs singing experience, 8 tenors, 12 baritones) were recruited to participate in the present study. Speaking fundamental frequency (FO), closed quotient (CQ), MPT (Maximum Phonation Time), breathing types, maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), and singers' formants were measured. In addition, vibratory patterns were observed using stroboscopy. Sfo, singing CQ, breathing types, formant frequency in singers' formants, MIP, MEP, and MPT were significantly different from gender to gender. Generally, singers' formants were observed in male singers and also the pattern of singers' formants was different between tenors and baritones. Lower singing CQ values were observed than speaking CQ values in the female singers (P<.001). Furthermore, MEP, MIP, and singing CQ were significantly lower for female singers than for males singers (P<.001). MPT and speaking FO, however, were not significantly different between tenors and baritones.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.23-23
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• 2017

Recent favor on high quality food and concern on food safety have demonstrated the superiority of Hanwoo (Korean native cattle). In general, the price of cow is higher than those of steer and bull, causing cheating issues in the market. Hence, this study is to discriminate genders of Hanwoo with identification of factors which highly influence gender discrimination based on the big-size deboning data. Totally, there were 31 variables in the deboning data, and we divided into them two categories: data obtained before and after deboning. Discriminant function analysis was then applied into the data to determined the accuracy of gender discrimination in Hanwoo. The result showed that Hanwoo could be classified by gender with 99.2% of accuracy when using all 31 variables. In detail, it was possible to identify 93 of 94 bulls (98.9%), 96 of 96 cows (100%) and 74 of 75 steers (98.7%). The most significant variables was chuck, sirloin, armbone shin, plates, retail and cuts percentage, sequentially. With variables obtainable before deboning, accuracies of classification were 91.5% for bulls, 92.7% for cows, and 89.3% for steers. The most significant variables was water, cold carcass weight and back-fat thickness. The discrimination accuracy was higher with data obtainable after deboning: bulls (98.9%), cows (99.0%) and steers (98.7%). In this case, chuck, sirloin and armbone shin were the factors determined the classification ability. This study showed that Hanwoo can be classified based on deboning data with appropriate statistics, further suggesting weight of cut of beef might be the standard for gender classification.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.223-231
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• 2002

Recently, work-related musculoskeletal disorders(WMSDs) have rapidly increased and have been a major issue in the field of industrial safety. Of several physical risk factors for WMSDs, which include postures, vibration, repetitive work, speed or acceleration of movements, etc., awkward postures have been known as one of the major causes of WMSDs. For reducing the potential for injury as a result of postures, cost effective quantification of the magnitude for physical exposure to poor working postures is important and needed. To do this, several postural classification schemes have been developed and used in industrial sites. It is known that perceived discomfort for joint motions and muscle strength for females were much less than those for males. However, the existing postural classification schemes were developed without considering these gender effects. This study aims to develop a new postural classification scheme for female workers, based on the perceived discomfort for joint motions. The result showed that there was significant difference between the schemes for female and male. It was also found that when compared with OWAS, RULA and REBA, postural load was quantified more precisely with the developed scheme. It is recommended that different schemes according to gender of workers involved in work be used in order to accurately evaluate postural load of work postures.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.169-174
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• 2018

There are many CCTV cameras connected to the video surveillance and monitoring center for the safety of citizens, and it is difficult for a few monitoring agents to monitor many channels of videos. In this paper, we propose an intelligent video surveillance system utilizing a safety map to efficiently monitor many channels of CCTV camera videos. The safety map establishes the frequency of crime occurrence as a database, expresses the degree of crime risk and makes it possible for agents of the video surveillance center to pay attention when a woman enters the crime risk area. The proposed gender classification method is processed in the order of pedestrian detection, tracking and classification with deep training. The pedestrian detection and tracking uses Adaboost algorithm and probabilistic data association filter, respectively. In order to classify the gender of the pedestrian, relatively simple AlexNet is applied to determine gender. Experimental results show that the proposed gender classification method is more effective than the conventional algorithm. In addition, the results of implementation of intelligent video security system combined with safety map are introduced.

• Imaging Science in Dentistry
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• v.47 no.3
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• pp.149-155
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• 2017

Purpose: The classification of impacted maxillary third molars(IMTMs) facilitates interdisciplinary communication and helps estimate the degree of surgical difficulty. Thus, this study aimed to develop a 3-dimensional classification of the position and depth of impaction of IMTMs and to estimate their prevalence with respect to gender and age. Materials and Methods: This cross-sectional retrospective study analyzed images in sagittal and coronal cone-beam computed tomography (CBCT) sections of 300 maxillary third molars. The proposed classification was based on 3 criteria: buccolingual position (buccal, lingual, or central), mesial-distal position (mesioangular, vertical, or distoangular), and depth of impaction (low, medium, or high). CBCT images of IMTMs were classified, and the associations of the classifications with gender and age were examined using analysis of variance with the Scheffe post-hoc test. To determine the associations among the 3 classifications, the chi-square test was used (P<.05). Results: No significant association of the classifications with gender was observed. Age showed a significant relationship with depth of impaction (P=.0001) and mesial-distal position (P=.005). The most common positions were buccal(n=222), vertical(n=184), and low (n=124). Significant associations among the 3 tested classifications were observed. Conclusion: CBCT enabled the evaluation of IMTMs in a 3-dimensional format, and we developed a proposal for a new classification of the position and depth of impaction of IMTMs.

• Korean Journal of Clinical Pharmacy
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• v.23 no.2
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• pp.114-122
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• 2013

Background: Drugs should be evaluated in appropriate subjects representing potential population to take the drugs. This study focuses on gender factor and aims to make known the appropriateness of considering gender difference on clinical evaluation of drug with domestic data related to drug use. Methods: To understand gender difference shown in drug use, three types of domestic statistical data (prevalence of chronic disease, number of outpatient with major concerning disease, and consumption of medicine) were analyzed and compared according to gender. Results: Three of fifteen chronic diseases which were analyzed, showed significantly higher prevalence in women than in men, and three were vice versa. Meanwhile, the sex ratio of outpatients was significantly different in 22 major concerning diseases. Among the drug groups coded by Anatomical Therapeutic Chemical (ATC) Classification System, the consumption of most drug groups was generally higher in women than in men except for one group coded G (genito-urinary system and sex hormones). Conclusion: Gender difference should be considered in domestic clinical evaluation of drug and domestic guidance for reflecting gender difference should be established.