• Journal of IKEEE
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• v.23 no.3
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• pp.777-784
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• 2019

A pre-fire awareness and automatic notification system are required because it is possible to minimize the damage if the fire situation is precisely detected after a fire occurs in a place where people are unusual or in a mountainous area. In this study, we developed a RaspberryPi-based fire recognition system using Faster-recurrent convolutional neural network (F-RCNN) and single shot multibox detector (SSD) and demonstrated a fire alarm system that works with power line communication. Image recognition was performed with a pie camera of RaspberryPi, and the detected fire image was transmitted to a monitoring PC through an inductive power line communication network. The frame rate per second (fps) for each learning model was 0.05 fps for Faster-RCNN and 1.4 fps for SSD. SSD was 28 times faster than F-RCNN.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.476-484
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• 2019

RFID yoking proof proves that a pair of tags is scanned at the same time. Since the tags scanned simultaneously by a single reader are adjacent to each other, the yoking proof is used in applications that need to check the physical proximity of tagged objects. Most of the yoking proof schemes require pre-knowledge on adjacent tags. If an error occurs in the process of collecting information about adjacent tags, all subsequent proofs will fail verification. However, there is no research that suggests specific methods for obtaining information about adjacent tags. In this study, I propose a tag proximity information acquisition scheme for a yoking proof. The proposed method consists of two steps: scanning area determination and scanning area verification. In the first step, the size and position of the area to scan tags is determined in consideration of position and transmission range of the tags. In the next step, whether tag scanning is performed within the scanning area or not is verified through reference tags of the fixed position. In analysis, I show that the determined scanning area assures acquisition of adjacent tag information and the scanning area verification detects deformation and deviation of the scanning area.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.58-66
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• 2019

Recognition of named entity such as proper nouns in conversation sentences is the most fundamental and important field of study for efficient conversational information prediction. The most important part of a task-oriented dialogue system is to recognize what attributes an object in a conversation has. The named entity recognition model carries out recognition of the named entity through the preprocessing, word embedding, and prediction steps for the dialogue sentence. This study aims at using user - defined dictionary in preprocessing stage and finding optimal parameters at word embedding stage for efficient dialogue information prediction. In order to test the designed object name recognition model, we selected the field of daily chemical products and constructed the named entity recognition model that can be applied in the task-oriented dialogue system in the related domain.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1262-1270
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• 2020

Recently, the smart video surveillance research, which has been receiving increasing attention, has mainly focused on the intruder detection and tracking, and abandoned object detection. On the other hand, research on real-time detection of stolen objects is relatively insufficient compared to its importance. Considering various smart surveillance video application environments, this paper presents two different types of stolen object detection algorithms. We first propose an algorithm that detects theft of statically and dynamically registered surveillance objects using a dual background subtraction model. In addition, we propose another algorithm that detects theft of general surveillance objects by applying the dual background subtraction model and Mask R-CNN-based object segmentation technology. The former algorithm can provide economical theft detection service for pre-registered surveillance objects in low computational power environments, and the latter algorithm can be applied to the theft detection of a wider range of general surveillance objects in environments capable of providing sufficient computational power.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.44-49
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• 2021

Recently, due to COVID-19, studies have been popularly worked to apply neural network to mask wearing automatic detection system. For applying neural networks, the 1-stage detection or 2-stage detection methods are used, and if data are not sufficiently collected, the pretrained neural network models are studied by applying fine-tuning techniques. In this paper, the system is consisted of 2-stage detection method that contain MTCNN model for face recognition and ResNet model for mask detection. The mask detector was experimented by applying five ResNet models to improve accuracy and fps in various environments. Training data used 17,217 images that collected using web crawler, and for inference, we used 1,913 images and two one-minute videos respectively. The experiment showed a high accuracy of 96.39% for images and 92.98% for video, and the speed of inference for video was 10.78fps.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.371-377
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• 2022

This study examines whether there are subjects and learners to pay attention to as 'processes' that have not been dealt with in Korean vocabulary education due to prioritizing learning outcomes, educational outcomes, and objects. In addition, the purpose of this study was to examine the educational value of the neologism and to suggest data construction method for it. Proposal to create a 'single-level list' of neologisms as a preliminary work to create a dictionary as a learning material to teach new words to academic purpose learners, taking neologism as the vocabulary in the blind spot and foreign academic purpose learners as learners in the blind spot stage. did The 'single-layered list' is to divide new words by period into coined words, meanings, culture, etc. and construct them as data. Through this study, we will help systematically teach Korean vocabulary by adding vocabulary to be learned as a 'process' to the results of Korean vocabulary education so far.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.519-525
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• 2022

The face detection task of detecting a person's face in an image is used as a preprocess or core process in various image processing-based applications. The neural network models, which have recently been performing well with the development of deep learning, are dependent on 2D images, so if noise occurs in the image, such as poor camera quality or pool focus of the face, the face may not be detected properly. In this paper, we propose a face detection method that uses depth information together to reduce the dependence of 2D images. The proposed model was trained after generating and preprocessing depth information in advance using face detection dataset, and as a result, it was confirmed that the FRN model was 89.16%, which was about 1.2% better than the RetinaNet model, which showed 87.95%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.49-59
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• 2023

Recently, attention to the pandemic situation represented by COVID-19 emerged problems caused by unexpected shortage of medical personnel. In this paper, we present a method for diagnosing the presence or absence of lesional sign on PA chest X-ray images as computer vision solution to support diagnosis tasks. Method for visual anomaly detection based on feature modeling can be also applied to X-ray images. With extracting feature vectors from PA chest X-ray images and divide to patch unit, region-specific abnormality can be detected. As preliminary experiment, we created simulation data set containing multiple objects and present results of the comparative experiments in this paper. We present method to improve both efficiency and performance of the process through hard masking of patch features to aligned images. By summing up regional specificity and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to previous studies. By aggregating region-specific and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to our last study.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.101-109
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• 2009

An encryption module is equipped basically at 8i version ideal of Oracle DBMS, encryption module, but a performance decrease is caused, and users are restrictive. We analyze problem of DB security by technology by circles at this paper whether or not there is an index search, object management disorder, a serious DB performance decrease by encryption, real-time data encryption beauty whether or not there is data approach control beauty circular-based IP. And presentation does the comprehensive security Frame Work which utilized the DB Masking technique that is an alternative means technical encryption in order to improve availability of DB security. We use a virtual account, and set up a DB Masking basis by security grades as alternatives, we check advance user authentication and SQL inquiry approvals and integrity after the fact through virtual accounts, utilize to method as collect by an auditing log that an officer was able to do safely DB.