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Full-Text Articles in Life Sciences
Apple Leaf Disease Detection And Classification Based On Transfer Learning, Cevher Özden
Apple Leaf Disease Detection And Classification Based On Transfer Learning, Cevher Özden
Turkish Journal of Agriculture and Forestry
The world population and the number of people affected by hunger constantly increases. Precision farming offers new solutions to a modern and more fertile production in agriculture. Early and in-place disease detection is one of the fields that recent studies have focused on. The present paper introduces a new approach to transfer learning in that training, validating and testing of the model have been made on images from different sources to see its effectiveness. Several optimization methods including the adaptation of a recent custom PowerSign optimization algorithm are compared in the study. Accordingly, the model with Adagrad optimizer produced more …
A Smart Agricultural Application: Automated Detection Of Diseases In Vine Leaves Usinghybrid Deep Learning, Ahmet Alkan, Muhammed Usame Abdullah, Hanadi̇ Omai̇sh Abdullah, Muhammed Assaf, Huiyu Zhou
A Smart Agricultural Application: Automated Detection Of Diseases In Vine Leaves Usinghybrid Deep Learning, Ahmet Alkan, Muhammed Usame Abdullah, Hanadi̇ Omai̇sh Abdullah, Muhammed Assaf, Huiyu Zhou
Turkish Journal of Agriculture and Forestry
This paper reports a study which utilizes deep learning for automated detection of the symptoms of diseases on vine leaves. Vine fruits or grapes are very important and have existed in Syria and surrounding areas (e.g., Turkey) for many years. Quality of vine fruits is also very important in grape production as it is consumed in these areas every day. The aim of this study is to improve diseasedetection accuracy in vine leaves and to develop a system to help Syrian and Turkish farmers and agricultural engineers to maintain the quality of grape production. In this study, over 1000 images …
Determination Of Some Physicomechanical And Biochemical Parameters Of Hazelnut (Corylus Avellana L.) Cultivars, Necati̇ Çeti̇n, Mehmet Yaman, Kevser Karaman, Bünyami̇n Demi̇r
Determination Of Some Physicomechanical And Biochemical Parameters Of Hazelnut (Corylus Avellana L.) Cultivars, Necati̇ Çeti̇n, Mehmet Yaman, Kevser Karaman, Bünyami̇n Demi̇r
Turkish Journal of Agriculture and Forestry
Hazelnut is one of the most popular nuts consumed by people; it has different cultivars in Turkey. The aim of the current study was to characterize some physicomechanical characteristics, shape features, color, and biochemical properties of 6 standard and 3 local hazelnut cultivars grown in Turkey. The shape and size properties of the samples were determined using image processing techniques as an alternative to conventional measurement methods. Additionally, principal component analysis (PCA) was used to classify the hazelnut samples in terms of the biochemical parameters of the hazelnut cultivars. According to the findings, the highest crude oil (63.25%) and lowest …
Design, Development, And Evaluation Of A Target Oriented Weed Control System Usingmachine Vision, Ömer Bariş Özlüoymak, Ali̇ Bolat, Ali̇ Bayat, Emi̇n Güzel
Design, Development, And Evaluation Of A Target Oriented Weed Control System Usingmachine Vision, Ömer Bariş Özlüoymak, Ali̇ Bolat, Ali̇ Bayat, Emi̇n Güzel
Turkish Journal of Agriculture and Forestry
The objective of the study was to develop and test an automatic machine vision-based spraying robot for the detection, tracking, and spraying of artificial weeds by using LabVIEW programming language. The greenness method was used to distinguish green objects in the image. A time-controlled spray nozzle was run according to the presence of an artificial weed and its coordinates. A mobile test bench was built and the spraying system with a webcam was operated at speeds of 0.42, 0.54, 0.66, 0.78, and 0.90 km h-1, so as to be able to see the performance of the system. The amount of …
Determination Of In-Row Seed Distribution Uniformity Using Image Processing, Engi̇n Çakir, İkbal Aygün, Arzu Yazgi, Yi̇ği̇t Karabulut
Determination Of In-Row Seed Distribution Uniformity Using Image Processing, Engi̇n Çakir, İkbal Aygün, Arzu Yazgi, Yi̇ği̇t Karabulut
Turkish Journal of Agriculture and Forestry
The objective of this study was to determine the seed distribution uniformity of seeding machines using a low sensitivity (maximum 300 frames per second (fps)) high-speed camera and image processing method for corn, cotton, and wheat seeds under laboratory conditions. For this purpose, a high-speed camera with 100, 200, and 300 fps was used to measure the seed drop from the seeding tube onto the sticky belt. Video images then were transferred to the image processing algorithm, from which seed distribution can be calculated. The calculated measurements were compared statistically with the measurements obtained from sticky belt tests. According to …