• Journal of IKEEE
• /
• v.22 no.3
• /
• pp.624-629
• /
• 2018

Classification of moving targets in Pulse Doppler Radar(PDR) for surveillance and reconnaissance purposes is generally carried out based on listening and training experience of Doppler audio signals by radar operator. In this paper, we proposed the automatic classification method to identify the class of moving target with Doppler audio signals using the Mel Frequency Cepstral Coefficients(MFCC) and the Hidden Markov Model(HMM) algorithm which are widely used in speech recognition and the classification performance was analyzed and verified by simulations.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.3
• /
• pp.91-98
• /
• 2016

Detection and classification of underwater objects in sonar imagery are challenging problems. This paper proposes a system that detects and identifies underwater objects at the sea floor level using a sonar image and image processing techniques. The identification process of underwater objects consists of two steps; detection of candidate regions and identification of underwater objects. The candidate regions of underwater objects are extracted by image registration through the detection of common feature points between the reference background image and the current scanning image. And then, underwater objects are identified as the closest pattern within the database using eigenvectors and eigenvalues as features. The proposed system is expected to be used in efficient securement of Q route in vessel navigation.

• The Journal of the Acoustical Society of Korea
• /
• v.38 no.5
• /
• pp.574-579
• /
• 2019

Snoring is a typical symptom of sleep disorder and it is important to identify the occurrence of snoring because it causes sleep apnea. In this paper, we proposes a residual convolutional neural network as an efficient snoring identification algorithm. Residual convolutional neural network, which is a structure combining residual learning and convolutional neural network, effectively extracts features existing in data more than conventional neural network and improves the accuracy of snoring identification. Experimental results show that the performance of the proposed snoring algorithm is superior to that of the conventional methods.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.921-930
• /
• 2020

The Counter-battery radar estimates the origin and impact point of the artillery by tracking the trajectory of the shell. In addition, it has the ability of identifying the type of weapon. Depending on the position between the shell and the radar, the detected signals appear differently. This has ambiguity to distinguish the type of shells. This paper compares fuzzy logic and artificial intelligence, which classifies type of shell using the parameter of signal processing step. According to the research result, artificial intelligence can improve identification rate of type of shell. The data used in the experiment was obtained from a live fire detection test.

• Journal of Broadcast Engineering
• /
• v.27 no.4
• /
• pp.519-526
• /
• 2022

Identifying and searching for characters appearing in scenes during multimedia video editing is an arduous and time-consuming process. Applying artificial intelligence to labor-intensive media editing tasks can greatly reduce media production time, improving the creative process efficiency. In this paper, a method is proposed which combines existing artificial intelligence based techniques to automate character recognition and search tasks for video editing. Object detection, face detection, and pose estimation are used for character localization and face recognition and color space analysis are used to extract unique representation information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2012.06a
• /
• pp.496-498
• /
• 2012

선박이 운항중 타선과의 충돌상황을 효과적으로 신속하게 파악하는 데 도움을 줌으로써 선박 충돌사고를 방지하기 위한 선박충돌위험도 식별시스템을 개발하였다. 지난 연구에서는, 고안된 시스템의 성능을 검증하기 위해 부산항에서 일어난 제품운반선과 화물선간의 충돌사고의 실제 AIS 데이터를 이용한 재생시뮬레이션을 수행한 바 있다. 본 논문에서는 선박충돌위험도 식별 시스템의 테스트베드를 구축하였고, 실제 해상에서 AIS 신호를 이용하여 성능을 검증해 보고자 하였다. 이를 위해, 군산항과 인천항의 연안여객선에 테스트베드를 장착하고, 실제 운항중 AIS 정보를 이용하여, 실시간으로 선박충돌위험도 식별시스템의 온보드 시험을 수행하였다. 본 논문에서는 선박충돌위험도 식별 시스템의 테스트베드의 특징과, 실제 해상에서 수행된 온보드 시험 결과에 대해 소개하였다.

• Resources Recycling
• /
• v.30 no.4
• /
• pp.3-10
• /
• 2021

The field of recycling for waste electronic components, which is the typical example of an urban mine, requires the development of useful sorting techniques. In this study, a sorter based on image identification by deep learning was developed to select electronic components into four groups. They were recovered from waste printed circuit boards and should be separated to depend on the difference after treatment. The sorter consists of a workstation with GPU, camera, belt conveyor, air compressor. A small piece (less than 3.5 cm) of electronic components on the belt conveyor (belt speed: 6 cm/s) was taken and learned as teaching data. The accuracy of the image identification was 96% as kinds and 99% as groups. The optimum condition of sorting was determined by evaluating accuracies of image identification and recovery rates by blowdown when changing the operating condition such as belt speed and blowdown time of compressed air. Under the optimum condition, the accuracy of image classification in groups was 98.7%. The sorting rate was more than 70%.

• The Journal of Society for e-Business Studies
• /
• v.16 no.3
• /
• pp.159-168
• /
• 2011

To identify fraud clicks in the Internet advertisement, existing studies have considered keyword, visit time, and client IP as an independent variable for the standard. These methods have limitations in identifying the fraud clicks that utilize automation tools, for they are methods based on client IP and human activities on the Internet. This paper proposes that fingerprinting values of the variable combination should be used to identify fraud clicks. The proposed model is composed of 3 stages and the fingerprinting values are compared with the other input data at each stage; IP fingerprinting in the first stage, IP and session data fingerprinting in the second stage, and session data and keyword fingerprinting in the third stage. We showed that the proposed model of the fraud click identification is more correct than existing methods through experiments according to the proposed scheme.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.3 no.1
• /
• pp.38-46
• /
• 2010

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about $5^{\circ}$horizontally and $8^{\circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.9
• /
• pp.82-88
• /
• 2016

The proposed new UCI syntax is compatible with the existing identifier and defines fixed length in such cases as printable ID, bar code and QR code which may entail better usage of identifier itself. For the compatibility, the identifiable metadata "key" is used for the existing UCI identifier and "UCI" element of metadata is defined for the new UCI identifier. The new UCI identifier plays roles of the resolution service and representation, and the old UCI identifier plays a role of internal DB management. Also, the object code has two types, meaningless and meaningful. The meaningful object code type can be used according the content classification standards in various field as comics, games, advertisement etc. The standardization activities can be supported by the root agency of UCI.