• Title/Summary/Keyword: Feature enhancement

Search Result 258, Processing Time 0.028 seconds

Small Target Detection Method Using Bilateral Filter Based on Surrounding Statistical Feature (주위 통계 특성에 기초한 양방향 필터를 이용한 소형 표적 검출 기법)

  • Bae, Tae-Wuk;Kim, Young-Taeg
    • Journal of Korea Multimedia Society
    • /
    • v.16 no.6
    • /
    • pp.756-763
    • /
    • 2013
  • Bilateral filter (BF), functioning by two Gaussian filters, domain and range filter is a nonlinear filter for sharpness enhancement and noise removal. In infrared (IR) small target detection field, the BF is designed by background predictor for predicting background not including small target. For this, the standard deviations of the two Gaussian filters need to be changed adaptively in background and target region of an infrared image. In this paper, the proposed bilateral filter make the standard deviations changed adaptively, using variance feature of mean values of surrounding block neighboring local filter window. And, in case the variance of mean values for surrounding blocks is low for any processed pixel, the pixel is classified to flat background and target region for enhancing background prediction. On the other hand, any pixel with high variance for surrounding blocks is classified to edge region. Small target can be detected by subtracting predicted background from original image. In experimental results, we confirmed that the proposed bilateral filter has superior target detection rate, compared with existing methods.

Performance Enhancement of Phoneme and Emotion Recognition by Multi-task Training of Common Neural Network (공용 신경망의 다중 학습을 통한 음소와 감정 인식의 성능 향상)

  • Kim, Jaewon;Park, Hochong
    • Journal of Broadcast Engineering
    • /
    • v.25 no.5
    • /
    • pp.742-749
    • /
    • 2020
  • This paper proposes a method for recognizing both phoneme and emotion using a common neural network and a multi-task training method for the common neural network. The common neural network performs the same function for both recognition tasks, which corresponds to the structure of multi-information recognition of human using a single auditory system. The multi-task training conducts a feature modeling that is commonly applicable to multiple information and provides generalized training, which enables to improve the performance by reducing an overfitting occurred in the conventional individual training for each information. A method for increasing phoneme recognition performance is also proposed that applies weight to the phoneme in the multi-task training. When using the same feature vector and neural network, it is confirmed that the proposed common neural network with multi-task training provides higher performance than the individual one trained for each task.

Implementation of persistent identification of topological entities based on macro-parametrics approach

  • Farjana, Shahjadi Hisan;Han, Soonhung;Mun, Duhwan
    • Journal of Computational Design and Engineering
    • /
    • v.3 no.2
    • /
    • pp.161-177
    • /
    • 2016
  • In history based parametric CAD modeling systems, persistent identification of the topological entities after design modification is mandatory to keep the design intent by recording model creation history and modification history. Persistent identification of geometric and topological entities is necessary in the product design phase as well as in the re-evaluation stage. For the identification, entities should be named first according to the methodology which will be applicable for all the entities unconditionally. After successive feature operations on a part body, topology based persistent identification mechanism generates ambiguity problem that usually stems from topology splitting and topology merging. Solving the ambiguity problem needs a complex method which is a combination of topology and geometry. Topology is used to assign the basic name to the entities. And geometry is used for the ambiguity solving between the entities. In the macro parametrics approach of iCAD lab of KAIST a topology based persistent identification mechanism is applied which will solve the ambiguity problem arising from topology splitting and also in case of topology merging. Here, a method is proposed where no geometry comparison is necessary for topology merging. The present research is focused on the enhancement of the persistent identification schema for the support of ambiguity problem especially of topology splitting problem and topology merging problem. It also focused on basic naming of pattern features.

Evaluation of Imaging Performance of Phase Shift Mask Depending on Reflectivity with Sub-resolution Assist Feature in EUV Lithography (SRAF를 적용한 극자외선 노광기술용 위상 변위 마스크의 반사도에 따른 이미징 특성 연구)

  • Jang, Yong Ju;Kim, Jung Sik;Hong, Seongchul;Cho, HanKu;Ahn, Jinho
    • Journal of the Semiconductor & Display Technology
    • /
    • v.14 no.3
    • /
    • pp.1-5
    • /
    • 2015
  • In photolithography process, resolution enhancement techniques such as optical proximity correction (OPC) and phase shift mask (PSM) have been applied to improve resolution. Especially, sub-resolution assist feature (SRAF) is one of the most important OPC to enhance image quality including depth of focus (DOF). However, imaging performance of the mask could be varied with the diffraction order amplitude changed by inserting SRAF. Therefore, in this study, we investigated the imaging properties and process margin of attenuated PSM with SRAF. Reflectivities of attenuated PSMs at 13.5 nm were 3, 6, 9% and simulation was performed by $PROLITH^{TM}$. As a result, aerial image properties and DOF as well as diffraction efficiency were improved by increasing the reflectivity of attenuated PSM. Additionally, printed critical dimension variations depending on SRAF width and space error were also reduced for attenuated PSM with high reflectivity. However, SRAF could be printed when reflectivity of attenuated PSM is high enough. In conclusion, optimization of reflectivity of attenuated PSM and SRAF to prevent side-lobe from being printed is needed to be considered.

Local Region Spectral Analysis for Performance Enhancement of Dementia Classification (인지증 판별 성능 향상을 위한 스펙트럼 국부 영역 분석 방법)

  • Park, Jun-Qyu;Baek, Seong-Joon
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.12 no.11
    • /
    • pp.5150-5155
    • /
    • 2011
  • Alzheimer's disease (AD) and vascular dementia (VD) are the most common dementia. In this paper, we proposed a region selection for classification of AD, VD and normal (NOR) based on micro-Raman spectra from platelet. The preprocessing step is a smoothing followed by background elimination to the original spectra. Then we applied the minmax method for normalization. After the inspection of the preprocessed spectra, we found that 725-777, 1504-1592 and 1632-1700 $cm^{-1}$ regions are the most discriminative features in AD, VD and NOR spectra. We applied the feature transformation using PCA (principal component analysis) and NMF (nonnegative matrix factorization). The classification result of MAP(maximum a posteriori probability) involving 327 spectra transformed features using proposed local region showed about 92.8 % true classification average rate.

The Design and Practice of Disaster Response RL Environment Using Dimension Reduction Method for Training Performance Enhancement (학습 성능 향상을 위한 차원 축소 기법 기반 재난 시뮬레이션 강화학습 환경 구성 및 활용)

  • Yeo, Sangho;Lee, Seungjun;Oh, Sangyoon
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.10 no.7
    • /
    • pp.263-270
    • /
    • 2021
  • Reinforcement learning(RL) is the method to find an optimal policy through training. and it is one of popular methods for solving lifesaving and disaster response problems effectively. However, the conventional reinforcement learning method for disaster response utilizes either simple environment such as. grid and graph or a self-developed environment that are hard to verify the practical effectiveness. In this paper, we propose the design of a disaster response RL environment which utilizes the detailed property information of the disaster simulation in order to utilize the reinforcement learning method in the real world. For the RL environment, we design and build the reinforcement learning communication as well as the interface between the RL agent and the disaster simulation. Also, we apply the dimension reduction method for converting non-image feature vectors into image format which is effectively utilized with convolution layer to utilize the high-dimensional and detailed property of the disaster simulation. To verify the effectiveness of our proposed method, we conducted empirical evaluations and it shows that our proposed method outperformed conventional methods in the building fire damage.

The Enhancement of intrusion detection reliability using Explainable Artificial Intelligence(XAI) (설명 가능한 인공지능(XAI)을 활용한 침입탐지 신뢰성 강화 방안)

  • Jung Il Ok;Choi Woo Bin;Kim Su Chul
    • Convergence Security Journal
    • /
    • v.22 no.3
    • /
    • pp.101-110
    • /
    • 2022
  • As the cases of using artificial intelligence in various fields increase, attempts to solve various issues through artificial intelligence in the intrusion detection field are also increasing. However, the black box basis, which cannot explain or trace the reasons for the predicted results through machine learning, presents difficulties for security professionals who must use it. To solve this problem, research on explainable AI(XAI), which helps interpret and understand decisions in machine learning, is increasing in various fields. Therefore, in this paper, we propose an explanatory AI to enhance the reliability of machine learning-based intrusion detection prediction results. First, the intrusion detection model is implemented through XGBoost, and the description of the model is implemented using SHAP. And it provides reliability for security experts to make decisions by comparing and analyzing the existing feature importance and the results using SHAP. For this experiment, PKDD2007 dataset was used, and the association between existing feature importance and SHAP Value was analyzed, and it was verified that SHAP-based explainable AI was valid to give security experts the reliability of the prediction results of intrusion detection models.

A Study on the Development of Design Support Program based upon Academic-Industrial Collaboration -Concentrated on furniture industry in Kimpo area- (산학협동 디자인 지원 프로그램 개발 연구 -김포지역 가구 산업체를 중심으로-)

  • 김국선
    • Archives of design research
    • /
    • v.15 no.1
    • /
    • pp.59-67
    • /
    • 2002
  • In accordance with the fast changing circumstance, universities are now reaching, beyond the education place of simple delivery of knowledge and exchange of information, to a place of developing a specialty program related with the region and industry to achieve a competitive edge in education. Through these academic-industrial collaboration program, special knowledge and human resources in the university are utilized in the society and it may contribute to the development of industry and breed of career people based upon the real job site can be achieved. In addition, through the practical operation of such developed program, university may contribute to the enhancement of the competitiveness of the corporation to the activation and acceleration of the regional economy and finally to the enhancement of competitiveness of national industry in international level. This study tries to develop 3 technical instruction and support program related with the legion and industry which may conform to the ideals of university and its goal of education and can provide a platform for the education that is closely related with the regional industry and real job site iud may cope actively with the upcoming knowledge society and fast changing regional circumstances. This study will make research and analyze needs of design support from the industry in order to develop a academic-industrial cooperative design support program for the furniture industry which conforms to the regional characteristic and feature and develop and present contents of program in three area of development of furniture design technology, build-up of furniture design information system and establishment of order based education system. The proposed program is supposed to be operated practically and effectively and contribute to the development of new product, to enhancement of company image and finally to the maximization of corporate profit. Also this study is epected to be used as an important material for establishment of order-based education system which confirms to the job site needs that may be analysed from feedback of product results and for practical learning.

  • PDF

The Line Feature Extraction for Automatic Cartography Using High Frequency Filters in Remote Sensing : A Case Study of Chinju City (위성영상의 형태추출을 통한 지도화 : 고빈도 공간필터 사용을 중심으로)

  • Jung, In-Chul
    • Journal of the Korean association of regional geographers
    • /
    • v.2 no.2
    • /
    • pp.183-196
    • /
    • 1996
  • The purpose of this paper is to explore the possibility of automatic extraction of line feature from Satellite image. The first part reviews the relationship between spatial filtering and cartographic interpretation. The second part describes the principal operations of high frequency filters and their properties, the third part presents the result of filtering application to the SPOT Panchromatic image of the Chinju city. Some experimental results are given here indicating the high feasibility of the filtering technique. The results of the paper is summarized as follows: Firstly the good all-purposes filter dose not exist. Certain laplacian filter and Frei-chen filter were very sensitive to the noise and could not detect line features in our case. Secondly, summary filters and some other filters do an excellent job of identifying edges around urban objects. With the filtered image added to the original image, the interpretation is more easy. Thirdly, Compass gradient masks may be used to perform two-dimensional, discrete differentiation directional edge enhancement, however, in our case, the line featuring was not satisfactory. In general, the wide masks detect the broad edges and narrow masks are used to detect the sharper discontinuities. But, in our case, the difference between the $3{\times}3$ and $7{\times}7$ kernel filters are not remarkable. It may be due to the good spatial resolution of Spot scene. The filtering effect depends on local circumstance. Band or kernel size selection must be also considered. For the skillful geographical interpretation, we need to take account the more subtle qualitative information.

  • PDF

Digital X-ray Imaging in Dentistry (치과에서 디지털 x-선 영상의 이용)

  • Kim Eun-Kyung
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
    • /
    • v.29 no.2
    • /
    • pp.387-396
    • /
    • 1999
  • In dentistry. RadioVisioGraphy was introduced as a first electronic dental x-ray imaging modality in 1989. Thereafter. many types of direct digital radiographic system have been produced in the last decade. They are based either on charge-coupled device(CCD) or on storage phosphor technology. In addition. new types of digital radiographic system using amorphous selenium. image intensifier etc. are under development. Advantages of digital radiographic system are elimination of chemical processing, reduction in radiation dose. image processing, computer storage. electronic transfer of images and so on. Image processing includes image enhancement. image reconstruction. digital subtraction, etc. Especially digital subtraction and reconstruction can be applied in many aspects of clinical practice and research. Electronic transfer of images enables filmless dental hospital and teleradiology/teledentistry system. Since the first image management and communications system(IMACS) for dentomaxillofacial radiology was reported in 1992. IMACS in dental hospital has been increasing. Meanwhile. researches about computer-assisted diagnosis, such as structural analysis of bone trabecular patterns of mandible. feature extraction, automated identification of normal landmarks on cephalometric radiograph and automated image analysis for caries or periodontitis. have been performed actively in the last decade. Further developments in digital radiographic imaging modalities. image transmission system. imaging processing and automated analysis software will change the traditional clinical dental practice in the 21st century.

  • PDF