• 한국정보통신학회논문지
• /
• 제26권3호
• /
• pp.381-388
• /
• 2022

인스턴스 분할에서 Mask-RCNN은 베이스 모델로 자주 사용된다. Mask-RCNN의 성능을 높이는 것은 파생된 모델에 영향을 미치기에 의미가 있다. Mask-RCNN에는 입력 이미지 크기를 배치 크기로 통일시키는 변환 모듈(transform module)이 있다. 이 논문에서는 Mask-RCNN의 성능 향상을 위해 변환 모듈의 크기 조정 부분에 딥러닝 기반 ASSR(Arbitrary-Scale Super-Resolution)을 적용하고, 스케일 정보를 모델의 IM(Integration Module)을 이용하여 주입한다. 제안하는 방법을 COCO 데이터세트에 적용하였을 때 인스턴스 분할 성능이 Mask-RCNN 성능보다 2.5 AP 높았다. 그리고 제안하는 IM 위치 최적화를 위한 실험에서는 FPN(Feature Pyramid Network)과 백본(backbone)이 결합하기 전의 'Top' 위치에 배치했을 때 가장 좋은 성능을 보였다. 따라서 제안하는 방법은 Mask-RCNN을 베이스 모델로 사용하는 모델들의 성능을 향상시킬 수 있다.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2004년도 춘계학술대회 논문집 반도체 재료 센서 박막재료 전자세라믹스
• /
• pp.97-100
• /
• 2004

We have grown GaN layers with in-situ SiN mask by metal organic chemical vapor deposition (MOCVD) and study the characteristic of the GaN layer. We have changed the deposition time of SiN mask from 45s to 5min and obtain th optimum condition in 45s. The PL intensity of GaN with SiN mask improved 2 times to that without SiN mask and the carrier concentraion increased from $3.5{\times}10^{16}cm^{-3}$ to $1.8{\times}10^{17}cm^{-3}$. We have thus shown that the SiN mask improved significantly the optical properties of the GaN layer.

• 한국언어정보학회:학술대회논문집
• /
• 한국언어정보학회 1998년도 Language, Information and Computation = Selected Papers from the 12th Pacific Asia Conference on Language, Information and Computation, Singapore
• /
• pp.283-294
• /
• 1998

• 대한의용생체공학회:의공학회지
• /
• 제16권2호
• /
• pp.239-248
• /
• 1995

The method of increasing signal to noise ratio (SNR) in a Hadamard transform spectrometer (HTS) is multiplexing. The multiplexing is executed by a mask. Conventional masks are mechanical or electro-optical. A mechanical mask has disadvantages of jamming and misalignment. A stationary electro-optical mask has a disadvantage of information losses caused by spacers which partition mask elements. In this paper, a mixed-concept electro-optical mask (MCEOM) is developed by expanding the length of a spacer to that of lon-off mask element. An MCEOM is operated by stepping a movable mask. 2N measurements are required for N spectrum estimates. The average mean square error (AMSE) using MCEQM is equal to that using a stationary electro-optical mask without spacers for large N. The cost of manufacturing an MCEOM is lower than that of producing a conventional electro-optical mask because an MCEOM needs only (N + 1)/2 on-off mask elements whereas the con¬ventional electro-optical mask needs N on-off mask elements. There are no information losses in the spectrometers having an MCEOM.

• Journal of information and communication convergence engineering
• /
• 제21권1호
• /
• pp.17-23
• /
• 2023

Recently, several high-performance instance segmentation models have used the Mask R-CNN model as a baseline, which reached a historical peak in instance segmentation in 2017. There are numerous derived models using the Mask R-CNN model, and if the performance of Mask R-CNN is improved, the performance of the derived models is also anticipated to improve. The Mask R-CNN uses interpolation to adjust the image size, and the input differs depending on the interpolation method. Therefore, in this study, the performance change of Mask R-CNN was compared when various interpolation methods were applied to the transform layer to improve the performance of Mask R-CNN. To train and evaluate the models, this study utilized the PennFudan and Balloon datasets and the AP metric was used to evaluate model performance. As a result of the experiment, the derived Mask R-CNN model showed the best performance when bicubic interpolation was used in the transform layer.

• 전자공학회논문지A
• /
• 제30A권9호
• /
• pp.46-58
• /
• 1993

Owing to the nature of locality in mask layouts, it appears that most mask layout problems can be solved by transforming a part of the given mask layout into a better layout segment continuously toward a global suboptimal solution. This notion of local transformation addresses major weak points of existing mask layout processing systems, which lack both extensibility and unifiability. This paper attempts to elaborate upon developing a new rule-based mask layout transformation system wherein most of the mask layout problems can be solved under the unified framework of local mask layout transformation. The rule-based mask layout transformation system is applicable to various mask layout problems such as net extraction, mask layout compaction, mask layout editing, and design rule checking. The experimental results show that the rule-based expert system approach is an efficient means of solving those mask layout problems, and thus confronting major drawbacks of existing layout processing systems.

• 대한전자공학회논문지
• /
• 제26권8호
• /
• pp.1247-1256
• /
• 1989

In this paper, we propose the dynamic scene segmentation algorithm using a cross mask and edge information. This method, a combination of the conventioanl feature-based and pixel-based approaches, uses edges as features and determines moving pixels, with a cross mask centered on each edge pixel, by computing similarity measure between two consecutive image frames. With simple calcualtion the proposed method works well for image consisting of complex background or several moving objects. Also this method works satisfactorily in case of rotaitional motion.

• Journal of information and communication convergence engineering
• /
• 제13권4호
• /
• pp.280-285
• /
• 2015

Double random phase encryption (DRPE) is one of the well-known optical encryption techniques, and many techniques with DRPE have been developed for information security. However, most of these techniques may not solve the fundamental security problem caused by using fixed phase masks for DRPE. Therefore, in this paper, we propose a key phase mask updating scheme for DRPE to improve its security, where a spatial light modulator (SLM) is used to implement key phase mask updating. In the proposed scheme, updated key data are obtained by using previous image data and the first phase mask used in encryption. The SLM with the updated key is used as the second phase mask for encryption. We provide a detailed description of the method of encryption and decryption for a DRPE system using the proposed key updating scheme, and simulation results are also shown to verify that the proposed key updating scheme can enhance the security of the original DRPE.

• 한국컴퓨터정보학회논문지
• /
• 제16권3호
• /
• pp.27-34
• /
• 2011

본 논문에서는 영상의 명암대비(contrast)를 개선시키는 언샾 마스킹 방법을 제안한다. 언샾 마스킹은 이미지가 가지고 있는 에지와 디테일 정보를 개선시키는데 일반적인 샤프닝 마스크 보다 효과적이기에 이에 관한 많은 연구가 있었다. 제안하는 방법은 방향성 정보를 이용한 블록 단위의 언샾 마스킹 방법으로 영상을 블록 단위로 분할하고 DCT(Discrete Cosine Transform)를 이용하여 각 블록에서 패턴의 방향성 정보를 얻어낸다. DCT 결과로부터 해당 블록들의 방향성 타입을 결정하고 이에 따라 언샾 마스크를 적응적으로 적용한다. 블록의 분류는 평탄영역, 텍스처, 에지 그리고 나머지 형태로 구분되어 진다. 평탄 영역에 속하는 블록은 잡음에 의한 영향을 줄이기 위해 언샾 마스킹을 적용하지 않으며 텍스처와 에지영역에 대해서는 고주파 성분을 강조하기 위해 블록타입에 맞는 적응적 언샾 마스킹을 적용한다. 실험을 통하여 영상에서 평탄 영역은 잡음에 의한 훼손을 줄이며 에지들이 포함된 텍스처 영역은 적응적으로 강조하여 시각적으로 우수한 명암대비 개선 결과를 얻을 수 있었다.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2019년도 춘계학술대회
• /
• pp.71-73
• /
• 2019

차량이 얼마나 존재하고 어디에 존재하는지는 교통정보를 반영하는 GeoAI 기반 도시 환경의 구현에서 필수적으로 파악되어야 할 요소이다. 본 논문에서는 객체 검출 및 추출에 유용한 딥러닝 모델인 Mask R-CNN을 이용하여 차량 데이터를 학습시키고 드론으로 촬영한 실제 항공 영상에서 차량 검출 유무를 검증하였다.