• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.113-119
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• 2023

In this paper, we propose an optimization of a pose estimation deep learning model for recognition of abnormal behavior in unmanned stores using radio frequencies. The radio frequency use millimeter wave in the 30 GHz to 300 GHz band. Due to the short wavelength and strong straightness, it is a frequency with less grayness and less interference due to radio absorption on the object. A millimeter wave radar is used to solve the problem of personal information infringement that may occur in conventional CCTV image-based pose estimation. Deep learning-based pose estimation models generally use convolution neural networks. The convolution neural network is a combination of convolution layers and pooling layers of different types, and there are many cases of convolution filter size, number, and convolution operations, and more cases of combining components. Therefore, it is difficult to find the structure and components of the optimal posture estimation model for input data. Compared with conventional millimeter wave-based posture estimation studies, it is possible to explore the structure and components of the optimal posture estimation model for input data using genetic algorithms, and the performance of optimizing the proposed posture estimation model is excellent. Data are collected for actual unmanned stores, and point cloud data and three-dimensional keypoint information of Kinect Azure are collected using millimeter wave radar for collapse and property damage occurring in unmanned stores. As a result of the experiment, it was confirmed that the error was moored compared to the conventional posture estimation model.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.158-164
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• 2002

This paper proposes the optimization of ultrasonic signal recognition in ferrite carbon steel weld zone using neural networks. For these purposes, the ultrasonic signals for defects as porosity, incomplete penetration and slag inclusion in the weld zone are acquired in the type of time series data. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The proposed neural networks system in this study can enhances performance of ultrasonic signal recognition.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.64-73
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• 1998

This paper is concerned with defects detection and evaluation of heat affected zone (HAZ) in austenitic stainless steel type 304 by ultrasonic wave and neural network. In experiment, the reflected ultrasonic defect signals from artificial defects (side hole, vertical hole, notch) of HAZ appears as beam distance of prove-defect, distance of probe-surface, depth of defect-surface on CRT. For defect classification simulation, neural network system was organized using total results of ultrasonic experiment. The organized neural network system was learned with the accuracy of 99%. Also it could be classified with the accuracy of 80% in side hole, and 100% in vertical hole, 90% in notch about ultrasonic pattern recognition. Simulation results of neural network agree fairly well with results of ultrasonic experiment. Thus were think that the constructed system (ultrasonic wave - neural network) in this work is useful for defects dection and classification such as holes and notches in HAZ of austenitic stainless steel 304.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1022-1024
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• 2009

Stereoscopic Images provide depth information with the relative distances between the objects in the images. There are many different ways to extract disparity maps from the visible spectral images. For the infrared spectral range, the same approach cannot be utilized for the innate low resolution and colorless features because typical methods require corresponding features between the images. The authors suggest a new approach that makes use of image segmentation to obtain depth information for stereoscopic millimeter-wave images. For image segmentation a selective visual attention model based on the theory of a feature-integration of attention is used. Experimental results show the proposed method provides reasonable depth information for object shape recognition and display.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.871-874
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• 1997

A new typed distance relaying scheme is proposed. Artificial neural networks are applied to the distance relaying system composed of pattern recognition based. The proposed distance relaying scheme have the two block of pattern recognition stages to estimate the fundamental frequency and to classify the fault types. The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.445-448
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• 2003

This paper presents a novel iris recognition method using wavelet transform and curve simplification. One-dimensional signals, which are calculated over circles on the iris, are decomposed into a multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting node points. The curve is simplified by progressively removing unimportant node points while keeping the shape of the curve. Finally, a small number of node points represent features of each signal. Experiment results show that the presented method results in good performance in various noise environments.

• Fashion & Textile Research Journal
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• v.15 no.5
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• pp.797-807
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• 2013

This study aims to provide basic information that would be useful to develop more specialized fashion design products for launching Korean Wave fashion, especially in Singapore market where Korean Wave culture has been expanding significantly. To identify recognition level of Korean Wave fashion, customer survey was conducted to females in their late 10s to early 20s. The analysis on the current fashion market also was made, which showed the result that the elegant style was dominant in the local fashion market. According to the customer survey result, K-pop was the most influential on Korean Wave. Amongst the female K-pop stars, 2NE1 was ranked the first who most of those surveyed wanted to copy her fashion style, and the ranking followed by Girl's Generation and BoA. With this result, it would be recommended to reflect K-pop star's style in designing fashion products as design and style turned out to be the most important factors that those surveyed considered upon clothing purchase. However, there should be various promotion activities in order to make Korea fashion brands known to the public because only 24.6% of those surveyed responded that they were aware of Korean fashion brands launched in Singapore market. Nevertheless, as those respondents were willing to buy Korean fashion brand products, there would be plenty of potential to succeed in Singapore market if there would be continuous efforts to raise Korean brand awareness.

• Journal of Veterinary Clinics
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• v.13 no.2
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• pp.171-176
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• 1996

In this study, dldctronic identification system of individual dairy cow was developed for autocatization of stoxkvreeding management. To automize the breeding management, it is necessary to obtain and analyze the individual information distinguished from others perferentially. Electronic identification system can distinguish individual livestock from others with electromagnetic wave signal recognition system. Electoronic identification system consists of transmitter transmitting the oscillated signal and receiver set. The transmitted signal from transmitter clung to individual livestock is received from the receiving antenna and the signal in different according to the established value of the register. By distinct signal recieved from the reciever, wi can distinguish the identity of a livestock from others clearly. This system can manage $2^{12}$ individuals with a reciever theoretically. However in order to reduce the errors by analogous signal, this system uses only triple number and can manage 1365 individuals with a reciever practically. This system can be connevtted to Max 232 and microcomputer for the breeding management efficiently.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.111-115
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• 2017

Terahertz waves are superior to conventional X-ray or Magnetic Resonance Tomography(MRI), and the amount of information that can be transmitted is as large as thousands of times that conventional X-ray or MRI. In addition, Terahertz waves have great performance in analyzing an object which have some layered structure. By using this advantage, we can extract the letters of a page by analyzing information such as absorption amount and reflection amount by irradiating a closed book with pulses of various frequencies within gap of a terahertz wave. However, in the image of each page using the Terahertz wave might be obtained various kinds of noise and the different character occlusion region. So, to extract letters from the terahertz image, we must take the noise and occlusion region away. We have been working to enhancement the image quality in various ways, and keep on studying de-noising processing for enhancement about the image quality and high resolution. Finally, we also keep on studying about OCR(Optical Character Recognition) technology, which based on pattern matching technique, to read letters.