• 반도체디스플레이기술학회지
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• 제8권2호
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• pp.59-62
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• 2009

In order to check the validation of LC simulation, 0.7 inch LCOS panel in full-HD resolution was fabricated and used for the electro-optical measurement. Compared the measured data with the calculated data, the averaged difference was 1.72% under 0 ~ +6 V bias on pixel electrode. To improve the optical characteristics of full-HD LCOS panel, the planar structure and trench structures (0.1 um, 0.2 um and 0.3 um-in-depth) between adjacent pixels were investigated with LC simulation. The planar structure showed the higher reflectance and faster reflectance-voltage response time than the trench structure. The optical fill factor and contrast ratio of planar structure were also higher than those of trench structures. As compared 1 um-in-depth trench structure resembled to the real structure with the planar structure, the optical fill factor was improved by 1.15% and the contrast ratio was improved by 5.26%. In order to minimize the loss of luminance and contrast ratio, the planar structure need to be applied between adjacent pixels.

• 한국정보통신학회논문지
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• 제13권3호
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• pp.531-536
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• 2009

본 논문에서는 개선된 회로를 적용한 $256{\times}256$ 픽셀 저항형 지문센서를 제안하고 있다. 단위 픽셀 수준의 센싱회로는 가변적인 전류를 전압으로 변환하여 이진 디지털 신호로 만든다. 정전기에 효과적으로 대처할 수 있는 인접 픽셀 간 전기적 차폐 레이아웃 구조를 제안하고 있다. 전체회로는 단위 센서 회로를 확장하여 ASIC 설계방식을 통하여 설계한 뒤 로직 및 회로에 대하여 모의실험을 하였다. 전체회로는 $0.35{\mu}m$ 표준 CMOS 공정규칙을 적용하여 센서블록은 전주문 방식을 적용하고 전체 칩은 자동배선 툴을 이용하여 반주문 방식으로 레이아웃을 실시하였다.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1425-1430
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• 2018

In this paper, we propose a CNN based deep learning algorithm for semantic segmentation of images. In order to improve the accuracy of semantic segmentation, we combined pixel level object classification and image level object classification. The image level object classification is used to accurately detect the characteristics of an image, and the pixel level object classification is used to indicate which object area is included in each pixel. The proposed network structure consists of three parts in total. A part for extracting the features of the image, a part for outputting the final result in the resolution size of the original image, and a part for performing the image level object classification. Loss functions exist for image level and pixel level classification, respectively. Image-level object classification uses KL-Divergence and pixel level object classification uses cross-entropy. In addition, it combines the layer of the resolution of the network extracting the features and the network of the resolution to secure the position information of the lost feature and the information of the boundary of the object due to the pooling operation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.335-336
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• 2007

A new current-programmed pixel circuit for activematrix organic light emitting diodes (AMOLEDs), based on Organic TFTs (OTFTs), is proposed and verified by SPICE simulations. The simulation results show that the proposed pixel circuit, which is a current mirror structure consisting of five Organic TFTs and one capacitor, has reliable linear characteristics between input current and output OLED current. Also, the threshold voltage degradation of Organic TFTs due to long time operation stress is well compensated to reliable values.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 및 기술 세미나 논문집 디스플레이 광소자
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• pp.42-42
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• 2008

Considerable attention has been focused on the applications of flexible liquid crystal (LC)-based displays because of their many potential advantages, such as portability, durability, light weight, thin packaging, flexibility, and low power consumption. To develop flexible LCDs that are capable of delivering high-quality moving images, like conventional glass-substrate LCDs, the LC device structure must have a stable alignment layer of LC molecules, concurrently support uniform cell gaps, and tightly bind two flexible substrates under external tension. However, stable LC molecular alignment has not been achieved because of the layerless LC alignment, and consequently high-quality images cannot be guaranteed. To solve these critical problems, we have proposed a PDMS pixel-wall based bonding method via the IB irradiation was developed for fasten the two substrates together strongly and maintain uniform cell gaps. The effect of the IB irradiation on PDMS with PI surface was also evaluated by side structure configuration and a result of x-ray photoelectron spectroscopic analysis of PDMS interlayer as a function of binder with substrates. large number of PDMS pixel-walls are tightly fastened to the surface of each flexible substrate and could maintain a constant cell gap between the LC molecules without using any other epoxy or polymer. To enhance the electro-optical performance of the LC device, we applied an alignment method that creates pretilt angle on the PI surface via ion beam irradiation. Using this approach, our flexible LCDs have a contrast ratio of 132:1 and a response time of about 15 ms, resulting in highly reliable electro-optical performance in the bent state, comparable to that of glass-substrate LCDs.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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• pp.1046-1049
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• 2006

We proposed a simplified fabrication structure and method which can provide separate Red (R), Green (G), Blue (B), and White (W) OLED pixels with 2 metal-mask changes in emitting layer fabrication inspired from the structure of multi-layer white OLED and carrier blocking mechanism. A red emission layer for the R and W pixel with 1st mask, and then a blue emission layer with hole blocking layer for the B and W pixel with 2nd mask, and finally a common green emission layer were deposited sequentially. We expect that this concept would be very useful to the actual fabrication of multi-color OLED display although additional optimization is needed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(3)
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• pp.153-156
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• 2000

A novel silicon retina chip based on the information processing in the vertebrate retina was designed. The chip has a novel wiring structure in which all pixels are connected through the channel of MOS transistors, which simplifies a wiring structure compared with conventional resistive networks. The proposed structure minimizes the pixel area and certainly increases a fill factor since each pixel consists of only two photodiodes and three MOS transistors. It also enables the chip to operate over a wide range of light intensity by adjusting its conductance with the gate voltage. Simulation results with SPICE showed that the chip could extract the edge of input images successfully.

• 대한전자공학회논문지SP
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• 제40권6호
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• pp.1-9
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• 2003

본 논문에서는 지문 영상의 컨벡스 (convex) 구조를 이용하여 특징점을 추출하는 방법을 제안하였다. 지문영상에서 융선은 일정한 방향성을 가지며 융선의 단면은 주기성이 있는 사인파로 간주할 수 있다. 사인파 신호에서 국부 최대 위치를 검출함으로써 대략적인 한 화소 단위의 융선 추출이 가능하며 사인파 신호의 볼록한 컨벡스는 융선 영역에 해당한다. 이러한 지문의 특징을 이용하여 특징점을 효과적으로 찾는 방법을 제안한다. 이 과정에서 파라미터를 없애고 계산량을 줄임으로써 다양한 환경의 시스템에 적용 가능함을 보였다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
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• pp.529-530
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• 2005

A voltage driving AMOLED(Active Matrix Organic Light Emitting Diode) is useful for large-sized, high resolution OLED display. The conventional 2-TFTs, 1-CAP AMOLED circuit suffer from the threshold voltage variation of TFT. In this paper, a new AMOLED structure is proposed. It is composed of 5-TFTs and 2-capacitors. It is described that the operating principle and the characteristics of the proposed structure and is verified the performance by HSPICE simulation. The result of simulation shows that the effect of the threshold voltage variation in this circuit, is able to neglect.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.98-108
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• 2023

This paper is an attempt to design segmentation method based on fully convolutional networks (FCN) and attention mechanism. The first five layers of the Visual Geometry Group (VGG) 16 network serve as the coding part in the semantic segmentation network structure with the convolutional layer used to replace pooling to reduce loss of image feature extraction information. The up-sampling and deconvolution unit of the FCN is then used as the decoding part in the semantic segmentation network. In the deconvolution process, the skip structure is used to fuse different levels of information and the attention mechanism is incorporated to reduce accuracy loss. Finally, the segmentation results are obtained through pixel layer classification. The results show that our method outperforms the comparison methods in mean pixel accuracy (MPA) and mean intersection over union (MIOU).