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      저자 : 허진경(JinKyoung Heo) (검색결과 5 건)
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      • 백본이 수정된 YOLOv3를 이용한 약용작물 병충해 탐지 AI 서비스 구현

        허진경(JinKyoung Heo),이근호(Geunho Lee) 한국정보기술학회 2022 Proceedings of KIIT Conference Vol.2022 No.12

        식물이 생산하는 화학 물질은 자신의 생존을 향상하게 하는 과정 과정에서 화학 물질이 더 많이 생산될 수 있다. 특히 약용으로 사용되는 천연 추출물을 다량 함유한 약용작물은 적은 노동력으로 농업 생산성을 최대화할 수 있다. 본 논문은 식물의 천연 추출물 함량을 높일 수 있는 환경적 요인을 알아보기 위한 과정에서 발생할 수 있는 병충해로 인한 피해를 줄이기 위해 인공신경망 객체탐지 알고리즘인 YOLOv3의 백본을 수정한 모델을 적용한 인공지능 모델과 탐지 서비스 구현을 제안한다. Chemicals produced by plants can be produced more in the process of improving their own survival. In particular, medicinal crops containing a large amount of natural extracts used for medicinal purposes can maximize agricultural productivity with less labor. This paper proposes an artificial intelligence model and detection service implementation with a modified model of YOLOv3, an artificial neural network object detection algorithm, to reduce damage caused by pests in the process of identifying environmental factors that can increase the natural extract content of plants.

      • KCI등재

        히스토그램 분포도 역추적 변경에 의한 영상 강조

        허진경(JinKyoung Heo),김향태(HyangTae Kim) 한국지능정보시스템학회 2004 지능정보연구 Vol.10 No.1

        It is very important part of pre-processing for get better results by image processing that get emphasized image by processing of source image. Emphasized image is not only good looking image but clear and sharp image. Emphasized images are used very useful data at contour extraction and image recognition in image processing. It have different image recognition by how much represent a origin scene in row quality image. Present algorithms that get emphasized premier image do not get clear picture of degree that want in various kind of images and there is shortcoming that need much process times being proportional size of picture quality or accumulation degree of histogram. In this paper, we propose method to change distribution chart that pixels occupy in histogram as subsequentness in reflex of various kinds as well as that picture quality reflex method to emphasize so that is suitable in practical use purpose originally of premier. Proposed algorithm re-allot histogram distribution by reverse tracking histogram. Experimental images are same result and take less processing time than histogram equalization.

      • KCI등재

        MANET에서 안전한 서비스 제공을 위한 On-demand 라우팅 프로토콜의 성능 비교

        허진경(JinKyoung Heo),양환석(HwanSeok Yang) 한국디지털콘텐츠학회 2009 한국디지털콘텐츠학회논문지 Vol.10 No.2

        MANET is network that attach importance to not only service of large network as internet but also support of communication among each nodes because infrastructure constitution is disadvantage econ omically or difficult physically. The most important part in protection of systems constitute MANET is that authenticate each nodes securely and offer reliable service. Well defined routing technique is necessity to this. In this paper, in order to offer safe service, we compare capacity of present security routing protocol, analyze to solve weakness of existing on-demand routing protocol and existing routing protocol and argue with study course of hereafter security routing protocol.

      • KCI등재

        인공신경망 YOLOv5 알고리즘을 이용한 밀싹 흰곰팡이 탐지 서비스 구현

        허진경(JinKyoung Heo) 한국정보기술학회 2022 한국정보기술학회논문지 Vol.20 No.11

        Many studies are being conducted to solve rural problems due to the decrease in the population of rural areas and aging. The most representative would be the promotion of smart farm-related projects. In addition, interest in functional crops that can contribute to increasing farm income is also increasing. Therefore, in this study developed a YOLOv5 based model that can detect white fungi early to improve the productivity and commerciality of wheat sprouts, which are functional crops. And through the performance evaluation, the result was obtained in which the mAP value was 0.714 when the IoU was 0.5 or higher. We developed a real-time white mold detection system using YOLOv5 based white mold detection model, MQTT service, and Java web application.

      • KCI등재

        약용작물의 유효성분 함량 예측을 위한 기계학습 모형의 최적화 및 요인 분석

        허진경(JinKyoung Heo) 한국정보기술학회 2022 한국정보기술학회논문지 Vol.20 No.12

        Biochemical components of plants have less side effects and chemical resistance than synthetic chemical components. Moreover, medicinal crops are attracting attention due to the development of herbal medicine technology. In addition, since intensive cultivation of medicinal crops is possible and cash exchangeability is expected, the impact on the agricultural economy is increasing. Therefore, in this paper, we confirm that the growth environment can affect the increase in active ingredient content through optimization of machine learning models, and propose a method to find the optimal growth environment through factor analysis. This paper selected wheatgrass as the target crop for the experiment. To determine whether the environment affects isoorientin, machine learning model was optimized, and factor analysis method is proposed to find a environment that can increase the content of isoorientin.

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