• International Journal of Advanced Culture Technology
• /
• 제9권1호
• /
• pp.190-195
• /
• 2021

Currently, one of the fields leading the 4th industrial revolution is the image recognition field of artificial intelligence, which is showing good results in many fields. In this paper, using is a YOLO V2 model, which is one of the image recognition models, we intend to classify and select into three types according to the characteristics of fruits. To this end, it was designed to proceed the number of iterations of learning 9000 counts based on 640 mandarin image data of 3 classes. For model evaluation, normal, rotten, and unripe mandarin oranges were used based on images. We as a result of the experiment, the accuracy of the learning model was different depending on the number of learning. Normal mandarin oranges showed the highest at 60.5% in 9000 repetition learning, and unripe mandarin oranges also showed the highest at 61.8% in 9000 repetition learning. Lastly, rotten tangerines showed the highest accuracy at 86.0% in 7000 iterations. It will be very helpful if the results of this study are used for fruit farms in rural areas where labor is scarce.

• 한국멀티미디어학회논문지
• /
• 제25권6호
• /
• pp.833-843
• /
• 2022

Based on the problems of untimely Expressway fire rescue and backward traditional fire rescue methods, an emergency fire fighting and inspection robot riding on expressway guardrail is designed. The overall mechanical structure design of emergency fire fighting and inspection robot riding on expressway guardrail is completed by using three-dimensional design software. The target fire detection is realized by using the target detection algorithm of Yolov5; By selecting a variety of sensors and using the control method of multi algorithm fusion, the basic function of robot on duty early warning is realized, and it has the ability of intelligent fire extinguishing. The BMS battery charging and discharging system is used to detect the real-time power of the robot. The design of the expressway emergency fire fighting and inspection robot provides a new technical means for the development of emergency fire fighting equipment, and improves the reliability and efficiency of expressway emergency fire fighting.

• International Journal of Advanced Culture Technology
• /
• 제10권1호
• /
• pp.294-301
• /
• 2022

COVID-19 is a crisis with numerous casualties. The World Health Organization (WHO) has declared the use of masks as an essential safety measure during the COVID-19 pandemic. Therefore, whether or not to wear a mask is an important issue when entering and exiting public places and institutions. However, this makes face recognition a very difficult task because certain parts of the face are hidden. As a result, face identification and identity verification in the access system became difficult. In this paper, we propose a system that can detect masked face using transfer learning of Yolov5s and recognize the user using transfer learning of Facenet. Transfer learning preforms by changing the learning rate, epoch, and batch size, their results are evaluated, and the best model is selected as representative model. It has been confirmed that the proposed model is good at detecting masked face and masked face recognition.

• 한국멀티미디어학회논문지
• /
• 제25권10호
• /
• pp.1524-1534
• /
• 2022

This study proposes the classification model of Minhwa genre based on object detection of deep learning. To detect unique Korean traditional objects in Minhwa, we construct custom datasets by labeling images using object keywords in Minhwa DB. We train YOLOv5 models with custom datasets, and classify images using predicted object labels result, the output of model training. The algorithm consists of two classification steps: 1) according to the painting technique and 2) genre of Minhwa. Through classifying paintings using this algorithm on the Internet, it is expected that the correct information of Minhwa can be built and provided to users forward.

• 한국산업융합학회 논문집
• /
• 제25권4_2호
• /
• pp.573-586
• /
• 2022

Corrosion can cause dangerous and expensive damage and failures of ship hulls and equipment. Therefore, it is necessary to maintain the vessel by periodic corrosion inspections. During visual inspection, many corrosion locations are inaccessible for many reasons, especially safety's point of view. Including subjective decisions of inspectors is one of the issues of visual inspection. Automation of visual inspection is tried by many pieces of research. In this study, we propose image preprocessing methods by image patch segmentation and thresholding. YOLOv5 was used as an object detection model after the image preprocessing. Finally, it was evaluated that corrosion detection performance using the proposed method was improved in terms of mean average precision.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
• /
• pp.529-530
• /
• 2021

본 논문에서는 MindWave와 AR 헤드셋 기기를 연동하여 자폐 스펙트럼 장애 아동이 불안감을 느낄 때 발산되는 뇌파 신호를 실시간으로 감지한다. 또한 실시간 객체 검출을 위한 YOLOv5 알고리즘을 통해 시각적 정보를 수집하여 해당 아동이 불안감을 느끼는 원인을 파악하고 이에 맞는 해결책을 AR 형태로 제시하며 자폐 스펙트럼 장애 아동이 불안감을 느끼면 보호자에게 알림을 전송하는 앱을 구현한다. 이를 통해 자폐 스펙트럼 장애 아동의 뇌파 안정과 정서 회복을 돕고 실생활에서 발생할 수 있는 돌발 상황을 방지할 수 있는 시스템을 제안한다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2021년도 추계학술발표대회
• /
• pp.1302-1304
• /
• 2021

본 프로젝트는 시각장애인의 도심이동 지원 및 횡단보도에서의 안전한 보행을 위해 고안되었다. 시각장애인용 글래스를 제작하여 Custom train 한 YOLOv5 와 Lidar 센서를 통해 횡단보도 내에 객체를 감지하면 위험 음성을 송출하고 안전하게 길을 건널 수 있도록 청각적으로 지도하였다. 또한 보호자용 앱을 구현하여 보호자의 불안감을 해소하고 안정감을 주고자 하였다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2022년도 추계학술발표대회
• /
• pp.758-760
• /
• 2022

본 연구는 머신러닝의 한 종류인 YOLOv5를 이용하여 기존 육안 선별작업을 자동화 하는 기계를 설계하는 것이다. 본 연구에서는 영상촬영과 선별작업을 진행하는 컨베이어 기구와 선별 프로그램을 제작하고, 모든 표면을 검사해 사과의 품질을 3단계로 구별하는 작업을 진행하였다. 결과적으로 투입된 사과의 품질을 성공적으로 분류 하였다.

• 국제학술발표논문집
• /
• The 9th International Conference on Construction Engineering and Project Management
• /
• pp.871-876
• /
• 2022

In the construction industry, fatal accidents related to scaffolds frequently occur. To prevent such accidents, scaffolds should be carefully monitored for their safety status. However, manual observation of scaffolds is time-consuming and labor-intensive. This paper proposes a method that automatically analyzes the installation status of scaffold joints based on images acquired from a Unmanned Aerial Vehicle (UAV). Using a deep learning-based object detection algorithm (YOLOv5), scaffold joints and joint components are detected. Based on the detection result, a two-stage rule-based classifier is used to analyze the joint installation status. Experimental results show that joints can be classified as safe or unsafe with 98.2 % and 85.7 % F1-scores, respectively. These results indicate that the proposed method can effectively analyze the joint installation status in UAV-acquired scaffold images.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2022년도 추계학술대회
• /
• pp.77-79
• /
• 2022

형태가 가변적인 영상을 감지하기 위해서는 많은 양의 관련 영상이 필요하다. 따라서 본 논문에서는 형태가 가변적인 영상 중 화재 영상을 GAN 알고리즘을 통해 증식시키고 이 영상을 이용해 AI 학습을 수행할 때의 검출률을 비교하여 GAN 알고리즘을 사용하여 증식된 이미지가 학습 데이터에 적합한지 분석하였다.