• Fisheries and Aquatic Sciences
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• v.2 no.2
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• pp.129-134
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• 1999

Haloptilus caribbeanensis Park, 1970 (Copepoda, Calanoida, Augaptilidae) is redescribed in detail on the basis of an adult female collected from Suruga Bay, Japan. This is the first record of the species from the Indo-Pacific region. Morphology of the Pacific specimen agrees well with that of the Caribbean Sea and Gulf of Mexico specimens, except for the numbers of mandibular teeth. The former has five teeth and the latter six teeth on mandible. The segmentation and segmental aesthetasc numbers of female antennules of H. caribbeanensis are compared with those of five species of Haloptilus (H. angusticeps, H. fons, H. longicomis, H. ornatus and H. spiniceps). These characters show morphological differentiation at the species level. H. caribbeanensis has no aesthetasc on the proximal segments II, IV, and VI of the female antennules.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.63-68
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• 2017

In this paper, we propose a bounding box prediction algorithm using multiple probability maps to improve object detection result of object detector. Although the performance of object detectors has been significantly improved, it is still not perfect due to technical problems and lack of learning data. Therefore, we use the result correction method to obtain more accurate object detection results. In the proposed algorithm, the preprocessed bounding box created as a result of object detection by the object detector is clustered in various form, and a conditional probability is given to each cluster to make multiple probability map. Finally, multiple probability map create new bounding box of object using morphological elements. Experiment results show that the newly predicted bounding box reduces the error in ground truth more than 45% on average compared to the previous bounding box.

• Speech Sciences
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• v.15 no.4
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• pp.67-81
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• 2008

The accuracy rate of P2G (Phoneme-to-Grapheme) is one of the important factors determining the quality of unlimited voice recognition (VR) systems. Few studies were, however, conducted to reduce ambiguities of a phoneme string which can be segmented into a variety of different linguistic units (i.e. morphemes, words, eo-jeols), thus be transformed into more than one grapheme string. This paper is a preliminary research for building a large knowledge base of those homonymic & heterographic units(HHUs), which will provide unlimited Korean VR systems with more accurate P2G information. This paper analyzes 2 main factors generating HHUs: (1) boundary determination of the prosodic unit; (2) its segmentation into linguistic units. In this paper, linguistic characteristics determining variable boundaries of a prosodic unit are investigated, and the ambiguity types of HHUs are classified in accordance with their morphological and syntactic structures as well as with the phonological rules governing them.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.335-338
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• 2002

This paper proposes some technical approaches for automatic detection of pulmonary nodules in chest X-ray images. We applied threshold technique for the lung field segmentation and extended the lung field by using morphological methods. A template matching technique was employed for automatic detecting nodules in lung area. Genetic algorithm(GA) was used in template matching(TM) to select a matched image from various reference patterns(simulated typical nodules). We eliminated the false-positive candidates by using histograms and contrasts. We used standard databases published by Japanese Society of Radiological Technology (JSRT) for correct results. Also we employ two-dimensional Gaussian distribution for some reference images because the shadow of lung nodules in radiogram generally shows the distributions. Nodules of about 89% were correctly detected by our scheme. The simulation results show that it is an effective method to indicate lesions on chest radiograms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.81-90
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• 1994

This paper proposes a motphological fast reconstructive filter (FRF) using up/down sampling techniques for reconstructive opening and closing, and a parallel structure for fast multiresolution decomposition. Compuer simulation shows that, compared with the conventional RF, the proposed FRF can reduce the processing time up to 8 times while it maintains a similar performance in reconstructed shapes. Further reduction in the decomposition time achieved by the paralellized algorithm combined with the FRF, which can be applied in areas such as defect detection, image segmentation, pattern recognition, etc.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.13-17
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• 2013

본 논문은 CRF기반 한국어 형태소 분석 및 품사 태깅 과정에서 발생하는 미등록 복합형태소를 분해하기 위한 단순하고 효과적인 방법을 제안한다. 제안 방법은 1) 복합형태소를 내용형태소와 복합기능형태소로 분리하는 단계, 2) 복합기능형태소를 분해하는 두 단계로 구성된다. 실험 결과, 제안 알고리즘은 Sejong데이터에 대해, 기존의 lattice HMM 대비 높은 복합형태소 분해 정확률 및 두드러진 속도 개선을 보여준다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.123-130
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• 2000

In this paper, we propose an extracting method of moving object contour using active contour model from image sequences acquired by fixed camera. We use an adaptive background model for robust processing in surrounding conditions. Object segmentation model detects pixels thresholded from local difference image between background and current image and extracts connected regions. Noises in boundary area of moving object we eliminated by morphological filter. The contour of segmented object is corrected by using active contour model for extracting accurate boundary of moving object. We apply the proposed method to highway image sequences and show the results of simulation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.397-398
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• 2019

망막혈관 영상에서(retinal image) 혈관의 모양 또는 생성변화를 효과적으로 검진하기 위해서 망막혈관을 자동적으로 분리하는 영상분할 기법의 개발은 매우 중요한 사안이다. 이를 위해서 주로 망막혈관영상의 잡음을 억제하고 또한 혈관의 명암대비도(contrast)를 증가시키는 전처리 과정을 거쳐서 혈관의 국부적인 화소값의 변화, 방향성을 판별하여 혈관을 자동적으로 검출하는 방법들이 제시되어왔으며 최근에는 합성곱 신경망(CNN) 딥러닝 학습모델을 활용한 망막혈관 분리 알고리즘들이 제시되고 있다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.202-210
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• 2019

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.