• E2M - 전기 전자와 첨단 소재
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• 제10권9호
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• pp.916-921
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• 1997

In this study Characteristics of 3-D underwater object recognition independent of translation using the self-made ultrasonic sensor fabricated with porous piezoelectric resonator and presented. The sensor was satisfied with requirement of ultrasonic sensor. The recognition rates for the training data and the testing data are 97.45 and 91.25[%] respectively using the self-made ultrasonic sensor and SCL(Simple Competitive Learning) neural network. According to the experimental results It is believed that the self-made ultrasonic sensor can be applied as sensor of SONAR system.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1996년도 추계학술대회 논문집
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• pp.316-319
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• 1996

In this study, characteristics of ultrasonic transducer fabricated with porous piezoelectric resonator are investigated, 3-D underwater object recognition using the self-made ultrasonic transducer and SOFM(Self-Organizing Feature Map) neural network are presented. The self-made transducer was satisfied the required condition of ultrasonic transducer in water, and the recognition rates for the training data and the testing data were 100 and 95.3% respectively. The experimental results have shown that the ultrasonic transducer fabricated with porous piezoelectric resonator could be applied for sonar system.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.67-70
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• 2022

NLP 분야에서 적극 활용되기 시작한 Transformer 모델을 Vision 분야에서 적용하기 시작하면서 object detection과 segmentation 등 각종 분야에서 기존 CNN 기반 모델의 정체된 성능을 극복하며 향상되고 있다. 또한, label 데이터 없이 이미지들로만 자기지도학습을 한 ViT(Vision Transformer) 모델을 통해 이미지에 포함된 여러 중요한 객체의 영역을 검출하는 saliency map을 추출할 수 있게 되었으며, 이로 인해 ViT의 자기지도학습을 통한 object detection과 semantic segmentation 연구가 활발히 진행되고 있다. 본 논문에서는 ViT 모델 뒤에 classifier를 붙인 모델에 일반 학습한 모델과 자기지도학습의 pretrained weight을 사용해서 전이학습한 모델의 시각화를 통해 각 saliency map들을 비교 분석하였다. 이를 통해, 클래스 분류 학습 기반 전이학습이 transformer의 saliency map에 미치는 영향을 확인할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.388-393
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• 1992

An infrared range finder using a self-mixing laser diode (SM-LD), which has been proposed and developed by the Authors, can measure not only a range of a moving target but its velocity simultaneously. In this paper, described is that the precise mode-hop pulse train can be obtained by employing a new signal processing circuit even when the backscattered light returning into the SM-LD is much more weaker. As a result, the distance to a tilted square sheet made from aluminium or white paper, which is placed 10 cm through 60 cm from the SM-LD, is measured with accuracy of a few percent even when the tilting angle is less than 75 degrees or 85 degrees, respectively. And in this paper, described is the range-image recognition of a plane object under the condition of standstill. The output laser beam is scanned by scanning two plane mirrors-equipped with each stepping motor. And we succeeded in the acquisition of the range-image of a plane object in a few tens of seconds. Furthermore, described is a feasibility study about the range-image recognition of a slowly moving plane object.

• 로봇학회논문지
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• 제18권3호
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• pp.346-351
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• 2023

With the release of numerous open driving datasets, the demand for domain adaptation in perception tasks has increased, particularly when transferring knowledge from rich datasets to novel domains. However, it is difficult to solve the change 1) in the sensor domain caused by heterogeneous LiDAR sensors and 2) in the environmental domain caused by different environmental factors. We overcome domain differences in the semi-supervised setting with 3-stage model parameter training. First, we pre-train the model with the source dataset with object scaling based on statistics of the object size. Then we fine-tine the partially frozen model weights with copy-and-paste augmentation. The 3D points in the box labels are copied from one scene and pasted to the other scenes. Finally, we use the knowledge distillation method to update the student network with a moving average from the teacher network along with a self-training method with pseudo labels. Test-Time Augmentation with varying z values is employed to predict the final results. Our method achieved 3rd place in ECCV 2022 workshop on the 3D Perception for Autonomous Driving challenge.

• 융합정보논문지
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• 제12권2호
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• pp.1-16
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• 2022

본 연구는 소셜네트워크서비스(Social Networking Service; SNS) 이용자들의 대상관계 요인들에 대해 파악하고 이들 요인이 즐거움과 자기효능감을 통해 이용자 만족에 얼마만큼의 영향을 미치는지에 대한 인과관계를 실증 연구함으로써 SNS에서 효과적이고 효율적인 발전방안을 제시한다. 본 연구모형을 소셜네트워크서비스를 이용한 경험이 있는 이용자들을 대상으로 설문조사를 실시하였다. PLS 구조방정식 모형을 이용하여 신뢰도 및 타당성 분석, 탐색적·확인적 요인분석, 판별 타당성, 적합도 검증, 직접·매개 경로분석을 실시하였다. 첫째, 비소외는 즐거움에 유의한 영향을 미쳤지만, 자기효능감에는 유의한 영향을 미치지 못했다. 둘째, 안정애착은 즐거움과 자기효능감에서 모두 유의한 영향을 미치지 못했다. 셋째, 사회적능력은 즐거움과 자기효능감에서 모두 유의한 영향을 미치지 못했다. 넷째, 자아중심성은 즐거움과 자기효능감에서 모두 유의한 영향을 미치지 못했다. 다섯째, 즐거움은 자기효능감과 이용자 만족에 모두 유의한 영향을 미쳤다. 여섯째, 자기효능감은 이용자 만족에 유의한 영향을 미쳤다.

• 전기전자학회논문지
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• 제27권3호
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• pp.251-257
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• 2023

본 논문에서는 비전 트랜스포머의 셀프 어텐션이 갖는 지역적 특징 부족을 개선하는 이중 구조 셀프 어텐션 방법을 제안한다. 객체 분류, 객체 분할, 비디오 영상 인식에서 합성곱 신경망보다 연산 효율성이 높은 비전 트랜스포머는 상대적으로 지역적 특징 추출능력이 부족하다. 이 문제를 해결하기 위해 윈도우 또는 쉬프트 윈도우를 기반으로 하는 연구가 많이 이루어지고 있으나 이러한 방법은 여러 단계의 인코더를 사용하여 연산 복잡도의 증가로 셀프 어텐션 기반 트랜스포머의 장점이 약화 된다. 본 논문에서는 기존의 방법보다 locality inductive bias 향상을 위해 self-attention과 neighborhood network를 이용하여 이중 구조 셀프 어텐션을 제안한다. 지역적 컨텍스트 정보 추출을 위한 neighborhood network은 윈도우 구조보다 훨씬 단순한 연산 복잡도를 제공한다. 제안된 이중 구조 셀프 어텐션 트랜스포머와 기존의 트랜스포머의 성능 비교를 위해 CIFAR-10과 CIFAR-100을 학습 데이터를 사용하였으며 실험결과 Top-1 정확도에서 각각 0.63%과 1.57% 성능이 개선되었다.

• Korean Journal of Mathematics
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• 제30권2호
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• pp.297-304
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• 2022

Fixed point theory has many useful applications in applied sciences. The object of this paper is to obtain fixed point for continuous self mappings in Hilbert C^*-module with rational conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권12호
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.

• 한국전산유체공학회지
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• 제22권1호
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• pp.88-94
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• 2017

The IR signal entering into a sensor is composed of the following components: the self-emitted component directly from the object surface, the reflected components of the solar and sky irradiance at the object surface, and the scattered component by the atmosphere without reference to any object surfaces. The self-emitted and reflected components from the object can be lowered by the atmospheric layer between the object and the IR sensor. The principle factors influencing the atmospheric transmittance are the air temperature, the relative humidity and the observation distance. Previous studies on IR signal transmission through the atmosphere are focused on uniform atmospheric conditions and the non-uniform nature of the atmosphere was not properly treated in modeling. In this study, we use the local atmospheric transmittance to simulate the non-uniform atmosphere in analyzing the IR signal from the object surface. The results show that the nonuniform analysis of the atmosphere becomes more important as the wavelength of IR signal increases.