• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.9-15
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• 1996

In this paper, we propose a new detector based on the median-shift sign. We call it the median-shift sign (MSS) detector, which is an extension of the classical sign detector. We first analyze the problem of detecting a dc signal in noise of known probability density function (pdf). The MSS detector with the optimum median-shift value, the optimum MSS detector, performs better than the sign detector in Gaussian noise: it has the best performance among the detectors compared in Laplacian and Cauchy noise. It is shown that the MSS detectors with constant median-shift values are nearly equal to the optimum MSS detector. We also analyze the problem of detecting a dc signal when only partial information is available on the noise. The MSS detectors with constant median-shift values are almost equal to the sign detector in Gaussian noise: they perform better than the sign and Wilcoxon detectors for most signal ranges in Laplacian and Cauchy noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1454-1460
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• 1998

In this ppaer, we propose a new detector based on the median-shift sign, and then investigate its asymptotic and finite sample-size performance. We call it the median-shift sign (MSS) detector, which is an extension of the classical sign detector. First, we consider the asymptotic opti$$\mu$ median shift values and their characteristics. Next, we consider the asymptotic relative efficiency of the MSS detectors. we then consider the problem of detecting known signals in noise of known probability density function, and the problem of detecting known signals when only partial information is available on the noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.620-627
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• 2016

This paper proposes an advanced detection technique for cable fault by eliminating the sign of reference signal in STDR(sequence time-domain reflectometry) and SSTDR(spread-spectrum time-domain reflectometry). The proposed fault-detection technique can eliminate the reference signal more effectively than the conventional one since the sign detector can approximately recover the distorted reference signal by cable and connector, and consequently, can detect the reflected signal by fault more effectively than the conventional one. Especially, it is shown that the error rate of proposed technique can be significantly lower than the conventional one in the case of far fault simulation.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.82-91
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• 2009

Sign language spotting is the task of detecting and recognizing the signs in a signed utterance. The difficulty of sign language spotting is that the occurrences of signs vary in both motion and shape. Moreover, the signs appear within a continuous gesture stream, interspersed with transitional movements between signs in a vocabulary and non-sign patterns(which include out-of-vocabulary signs, epentheses, and other movements that do not correspond to signs). In this paper, a novel method for designing a threshold model in a conditional random field(CRF) model is proposed. The proposed model performs an adaptive threshold for distinguishing between signs in the vocabulary and non-sign patterns. A hand appearance-based sign verification method, a short-sign detector, and a subsign reasoning method are included to further improve sign language spotting accuracy. Experimental results show that the proposed method can detect signs from continuous data with an 88% spotting rate and can recognize signs from isolated data with a 94% recognition rate, versus 74% and 90% respectively for CRFs without a threshold model, short-sign detector, subsign reasoning, and hand appearance-based sign verification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2339-2347
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• 1997

The performance of the adaptive noise canceller using LMS algorithm is degraded by the gradient noise due to target speech signals. An adaptive noise canceller with speech detector was proposed to reduce this performande degradation. The speech detector utilized the adaptive prediction-error filter adapted by the NLMS algorithm. This paper discusses to enhance the performance of the adaptive noise canceller forthecorlored noise. The affine projection algorithm, which is known as faster than NLMS algorithm for correlated signals, is used to adapt the adaptive filter and the adaptive prediction error filter. When the voice signals are detected by the speech detector, coefficients of adaptive filter are adapted by the sign-error afine projection algorithm which is modified to reduce the miaslignment of adaptive filter coefficients. Otherwirse, they are adapted by affine projection algorithm. To obtain better performance, the proper step size of sign-error affine projection algorithm is discussed. As resutls of computer simulation, it is shown that the performance of the proposed ANC is better than that of conventional one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.990-996
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• 2015

This paper proposes an enhanced scheme adding a sign detector at the front of the correlator in STDR (sequence time domain reflectometry) system. We have executed simulations to show the improvement of detection performance in two fault types and various fault locations. Consequently, it can be shown that the proposed scheme improves the detection performance of the location of far-fault without increasing the computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.5
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• pp.445-448
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• 1991

The two-sample locally optimum rank detection scheme is obtained which uses rank and sign statistics for detection of random signals in additive noise. It is shown that the detector is similar in structure to the locally optimum detector for random signals and to the one-sample locally optimum rank detector for random signals. It is also shown that the detector is a generalization of the two-sample locally optimum rank detector for known signals. In addition , the problem of two-sample locally optimum rank detection of random signals in multiple input case is considered briefly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.631-653
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• 2020

Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.29-32
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• 2000

We proposed a neural network based “left shoulder”detector. The auto-associative neural network was trained with the “left shoulder”patterns obtained from the Korea Composite Stock Price Index, and then tested out-of-sample with a reasonably good result. A hypothetical investment strategy based on the detector achieved a return of 132% in comparison with 39% return from a buy and hold strategy

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.921-926
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• 2003

This paper describes a new type of the spatial filter detector (SFD) with variable and multi-valued weighting function. This SFD called variable spatial filter detector with multi-valued weighting function (VSFDwMWF) uses current-mode circuits for noise resistance and high-resolution weighting values. Total weighting values consist of 7bit, 6-signal bit and 1-sign bit. We fabricate VSFDwMWF chip using Rohm 0.35${\mu}$m CMOS process. VSFDwMWF chip includes two-dimensional 10${\times}$13 photodiode array and current-mode weighting control circuit. Simulation shows the weighting values are varied and multi-valued by external switching operation. The layout of VSFDwMWF chip is shown.