Computer Science-AGH最新文献_第8页

Derin öğrenme ağları kullanılarak mısır yapraklarında hastalık tespiti

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.989305

M. Göksu, Kubilay Muhammed Sünnetci, Ahmet Alkan

{"title":"Derin öğrenme ağları kullanılarak mısır yapraklarında hastalık tespiti","authors":"M. Göksu, Kubilay Muhammed Sünnetci, Ahmet Alkan","doi":"10.53070/bbd.989305","DOIUrl":"https://doi.org/10.53070/bbd.989305","url":null,"abstract":"— Nowadays, people need easy access to basic nutrients to live a healthy life. In addition to providing calories that can meet the physiological needs of human beings, maize, which is one of the basic foods, contains valuable minerals and vitamins such as vitamin B6, sodium, magnesium, zinc, potassium, calcium, vitamin A. As a result of the increase in the world population in the world and our country, the need for maize is increasing day by day. Herein, it is important to detect the diseases seen in maize leaves that reduce the efficiency of maize production. Thanks to the developing technologies, producers should be encouraged by using technological opportunities in maize cultivation. In the study, it is aimed to detect maize rust, gray leaf spot, and leaf blight on maize leaves. In addition, two models based on the EfficientNetB5 network and convolutional neural network have been developed to detect diseases found in maize leaves using deep learning methods. To increase the performance metrics of created models, the number of images has been increased by using data augmentation techniques (mirror, rotation, scale). From the results, it is seen that the prediction success rates obtained in the EfficientNetB5 transfer learning model and the developed deep learning model are equal to 92.12% and 89.88%, respectively.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2021-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44694138","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: 2

Hibrid 3B-2B ESA Mimarisi Kullanılarak Hiperspektral Uzaktan Algılama Görüntülerinin Sınıflandırılması

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.989159

Hüseyin Fırat, M. Uçan, D. Hanbay

引用次数: 0

Derinlemesine Özellik Piramit Ağı Kullanarak Yüzey Hata Tespiti DerinlemesineÖzellik Piramit AğıKullanaak Yüzey Hata Tespiti

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.990950

Hüseyin Üzen, İlhami Sel, Muammer Türkoğlu, D. Hanbay

引用次数: 0

Merkezi Simetrik Yerel İkili Örüntü Temelli Görüntü Sahteciliği Tespiti 中心对称本地次映像基础映像身份验证桌面

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.990064

Bilgehan Gürünlü, Serkan Öztürk

引用次数: 0

Optimizasyonun Optimizasyonu Yaklaşımıyla Dağılım Fonksiyonu Tabanlı Kral Kelebeği Optimizasyon Algoritmasının Performansının Artırılması 加强基于King’s Club分布函数的优化算法的性能逼近优化

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.990245

Mehmet Akpamukçu, Abdullah Ateş

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引用次数: 1

Makine Öğrenmesi Yöntemlerinin Felç Riskinin Belirlenmesinde Performansı: Karşılaştırmalı bir çalışma 机器学习方法常见风险的定义：比较研究

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.990530

Özer Oğuz, Suat Bayir, Hasan Badem

引用次数: 0

Derin Öğrenme Yöntemleri ile Sıcaklık Tahmini: Diyarbakır İli Örneği

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Computer Science-AGH Pub Date : 2021-09-16 DOI: 10.53070/bbd.990966

Aynur Sevinç, Buket Kaya

引用次数: 2

A Comparative Performance Evaluations of SC and MC VLC Systems in Underwater Environments 水下环境下SC与MC VLC系统性能比较研究