• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.19-24
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• 2024

It is not an exaggeration to say that a single fire causes a lot of damage, so fires are one of the disaster situations that must be alerted as soon as possible. Various technologies have been utilized so far because preventing and detecting fires can never be completely accomplished with individual human efforts. Recently, deep learning technology has been developed, and fire detection systems using object detection neural networks are being actively studied. In this paper, we propose a new fire detection system that improves the previously studied fire detection system. We train the YOLOv8 model using refined datasets through improved labeling methods, derive results, and demonstrate the superiority of the proposed system by comparing it with the results of previous studies.

• Journal of Broadcast Engineering
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• v.4 no.1
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• pp.22-31
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• 1999

Moving object tracking improves the efficiency and qualification for observation system, broadcasting system, video conference, etc. This paper propcses an improved Bayes decision method for detecting and tracking moving objects in active camera environment. The Bayes decision based tracking approach finds the region of moving objects by analyzing the image sequences statistically. The propcsed algorithm regenerates the probability density function to accord with moving objects and background for active camera. Experimental results show that the algorithm is accurate. reliable and noise resistant. The result is compared with those of the conventional methods.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.229-233
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• 2012

A RFID system is a technology for detecting information on an object through wireless communication between a tag on the object and a reader, and its applications are being expanded to various areas. Because of its wireless communication, however, there are many vulnerabilities in security. Until now, many studies have been executed in order to solve problems related to the security and stability of RFID. In order to resolve vulnerabilities in existing security methods for privacy protection, this study proposed an authentication protocol that uses hash values received from tags and random numbers. When the proposed protocol was implemented, it was safe from various types of attacks between tag and reader and between reader and DB. Furthermore, compared to recently proposed protocols, it could implement a RFID system with enhanced security and less computation in tags.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.565-568
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• 1998

In this paper, we implemented the electornic moving aid system for safe walking of the blind. An obstacle detecting of each sector used ultrasound and a distance measurement used time of flight. The alarm is designed to have a sound and a tactile function that can be selected on an user's convenience. This system can detect and obstacle of upward, forward, downward and optimally warn to the blind with vibration, beep sound by appling warning algorithm on object detection. Experimental testing and performance evaluation have been successfully carried out with a prototype cane, and the experiment shows the capability of the function to detect unknown objects within an assigned distance, under knees, over head height, and crushed puddles.

• Journal of Power System Engineering
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• v.3 no.2
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• pp.64-69
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• 1999

The paper shows a result for development of BLDC motor drive by using a resolver as position detection sensor. The developed drive use a method detecting rotor position based on HSI interrupt function of microprocessor without a specialized counting circuit. The algorithm generating three-phase PWM wave to change switching voltage and current is realized based on single chip microprocessor. The PWM generating part and position counting circuit are realized by software technique without usage of conventional analogue circuit or object-oriented chips. So the drive system become compact. The effectiveness of the developed drive is verified by experimented results of speed response for step reference input.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.85-90
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• 2021

A ADAS(Advanced Driver Assistance System) for the safe driving is an important area in autonumous car. Specially, a ADAS software using an image sensors attached in previous car is low in building cost, and utilizes for various purpose. A algorithm for detecting the break-lamp from the tail-lamp of preceding vehicle is proposed in this paper. This method can perceive the driving condition of preceding vehicle. Proposed method uses the YOLO techinicque that has a excellent performance in object tracing from real scene, and extracts the intensity variable region of break-lamp from HSV image of detected vehicle ROI(Region Of Interest). After detecting the candidate region of break-lamp, each isolated region is labeled. The break-lamp region is detected finally by using the proposed selective-attention model that percieves the shape-similarity of labeled candidate region. In order to evaluate the performance of the preceding vehicle break-lamp detection system implemented in this paper, we applied our system to the various driving images. As a results, implemented system showed successful results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1267-1279
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• 2014

In this paper, we suggest the development of object detection systems for the safety of the ship through the study of the properties of short-range radar. Many of the short-range radars developed for special purpose like cars has cheaper price advantages but it is not proper to every application. In order to overcome such obstacles we need to analysis data from experiments in various environments and feature analysis of the device is essential. Also, the data clustering algorithms to display correct classified moving objects is necessary. In this paper we propose the advanced fast moving object detection system using short range radars with better detection accuracy. And we proposed a clustering algorithm using the value of the RCS and the speed and trajectory information of the radar data that are reflected.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.364-367
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• 2008

Earthwork is very equipment-intensive task and researches related to automated excavation have been conducted. There is an issue to secure the safety for an automated excavating system. Therefore, this paper focuses on how to improve safety for semi- or fully-automated backhoe excavation. The primary objective of this research is to develop object detection algorithm for automated safety system in excavation work. In order to satisfy the research objective, a diverse sensing technologies are investigated and analysed in terms of functions, durability, and reliability and verified its performance by several tests. The authors developed the objects detecting algorithm for user interface program using laser sensor. The results of this study would be the basis for developing the automated object detection system.