International Conference on Computer, Control, Informatics and its Applications最新文献

Deep Learning for Plant Classification in Precision Agriculture 基于深度学习的精准农业植物分类

International Conference on Computer, Control, Informatics and its Applications Pub Date : 2019-10-01 DOI: 10.1109/IC3INA48034.2019.8949612

Carlos A. Mamani Diaz, Edgar E. Medina Castaneda, Carlos A. Mugruza Vassallo

{"title":"Deep Learning for Plant Classification in Precision Agriculture","authors":"Carlos A. Mamani Diaz, Edgar E. Medina Castaneda, Carlos A. Mugruza Vassallo","doi":"10.1109/IC3INA48034.2019.8949612","DOIUrl":"https://doi.org/10.1109/IC3INA48034.2019.8949612","url":null,"abstract":"Deep learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multidisciplinary agriculture technologies domain. In this research, we present a deep learning classification system of diverse plants, in order to enable precision agriculture applications. This classification problem was achieved thanks to the public dataset “Plant Seedlings Dataset”, which contains images of approximately 960 unique plants belonging to 12 species at several growth stages. The database has been from Aarhus University Flakkebjerg Research Station in collaboration between the University of Southern Denmark and Aarhus University. A classification comparison was used to determinate which of three pre-trained models; InceptionV3, VGG16 and Xception; reach the best accuracy performance for the database used in this work. Results determined that (1) Xception was the best model for plant classification obtaining 86.21%, overcoming other networks in 7.37% with a time processing around 741 seconds. (2) GPU hardware changes the classification model results impacting strongly in their accuracy score.","PeriodicalId":118873,"journal":{"name":"International Conference on Computer, Control, Informatics and its Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130695068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

HFMS: Soft for Calculating and Simulating Harmonics Distortion and Passive Filters HFMS:计算和模拟谐波失真和无源滤波器的软件

International Conference on Computer, Control, Informatics and its Applications Pub Date : 2018-11-01 DOI: 10.1109/IC3INA.2018.8629511

Haposan Yoga Pradika Napitupulu, C. G. Irianto

{"title":"HFMS: Soft for Calculating and Simulating Harmonics Distortion and Passive Filters","authors":"Haposan Yoga Pradika Napitupulu, C. G. Irianto","doi":"10.1109/IC3INA.2018.8629511","DOIUrl":"https://doi.org/10.1109/IC3INA.2018.8629511","url":null,"abstract":"Due to harmonics phenomenon occurs on power system, harmonics filter needs to be installed into power system to mitigate and suppress harmonics distortion. In order to know the effect of installing harmonics filter, feasibility study needs to be done. Before conducting the study, some parameters and real harmonics data have to be measured and collected from power system, then input them into software for simulation. Most software used in feasibility study has been developed such as ETAP, PSIM, OrCAD, DigSILET, etc. Unfortunately, those software programs only provide the harmonics data of power electronics from their library and can’t conduct simulation using measured harmonics data from real condition on the power system. This paper contributes the development of a new software, Harmonics Filter Modelling Software (HFMS), which has been developed especially for simulating the harmonics distortion based on measured data on power system. This helps engineer to make feasibility study more accurately because it uses measured data from real condition on power system. In addition, HFMS is capable to compare the harmonics measured data with the harmonics limits based on standard IEEE 519TM-2014. It is also adequate to calculate four kinds of harmonics passive filters (single tuned filter, double tuned filter, damped-type double tuned filter, and c-type filter) automatically based on measured data. Last, it is able to simulate the effect after the filter is installed into the power system. HFMS has been validated using PSIM software and the result shows that HFMS works properly and has similar result.","PeriodicalId":118873,"journal":{"name":"International Conference on Computer, Control, Informatics and its Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114699402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Foreword from conference chair 由会议主席作序

International Conference on Computer, Control, Informatics and its Applications Pub Date : 2013-11-01 DOI: 10.1109/IC3INA.2013.6819132

A. Hadiana

引用次数: 0

Keynote: Computer Science 4.0: Old wine in new bottles? 主题演讲:计算机科学4.0:新瓶装旧酒?

International Conference on Computer, Control, Informatics and its Applications Pub Date : 1900-01-01 DOI: 10.1109/IC3INA48034.2019.8949608

J. M. Gómez-Berbís

引用次数: 0