Scopus
YÖKSİS DOI Eşleşti
SJR Q1
Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis
Computers and Electronics in Agriculture · Mayıs 2011
YÖKSİS Kayıtları
Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis
Computers and Electronics in Agriculture · 2011 SCI-Expanded
Prof. Dr. ŞAKİR TAŞDEMİR →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis
2011 ISSN: 01681699 SCI-Expanded
Prof. Dr. ŞAKİR TAŞDEMİR →
Towards a real-time sorting system: Identification of vitreous durum wheat kernels using ANN based on their morphological, colour, wavelet and gaborlet features
2019 ISSN: 0168-1699 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
Generating of land suitability index for wheat with hybrid system aproach using AHP and GIS
2019 ISSN: 0168-1699 SCI-Expanded
Prof. Dr. MERT DEDEOĞLU →
Multiclass Classification of Dry Beans Using Computer Vision and Machine Learning Techniques
2020 ISSN: 0168-1699 SCI-Expanded Q1
Doç. Dr. MURAT KÖKLÜ →
Classification of Rice Varieties with Deep Learning Methods
2021 ISSN: 0168-1699 SCI-Expanded Q1
Dr. Öğr. Üyesi İLKAY ÇINAR →
Dry bean cultivars classification using deep cnn features and salp swarm algorithm based extreme learning machine
2023 ISSN: 0168-1699 SCI-Expanded Q1
Dr. Öğr. Üyesi İLKAY ÇINAR →
Dry Bean Cultivars Classification Using Deep CNN Features and Salp Swarm Algorithm Based Extreme Learning Machine
2023 ISSN: 0168-1699 SCI-Expanded Q1
Doç. Dr. MURAT KÖKLÜ →
Classification of Rice Varieties with Deep Learning Methods
2021 ISSN: 0168-1699 SCI-Expanded Q1
Doç. Dr. MURAT KÖKLÜ →
Towards a real-time sorting system: Identification of vitreous durum wheat kernels using ANN based on their morphological, colour, wavelet and gaborlet features
2019 ISSN: 0168-1699 SCI-Expanded Q1
Dr. Öğr. Üyesi ESRA KAYA ERDOĞAN →
Dry bean cultivars classification using deep cnn features and salp swarm algorithm based extreme learning machine
2023 ISSN: 0168-1699 SCI-Expanded Q1
Doç. Dr. İLKER ALİ ÖZKAN →
Makale Bilgileri
ISSN01681699
Yayın TarihiMayıs 2011
Cilt / Sayfa76 · 189-197
Scopus ID2-s2.0-79955962482
Özet
In this study, the body measurements (BMs) of Holstein cows were determined using digital image analysis (IA) and these were used to estimate the live weight (LW) of each cow. For this purpose, an image capture arrangement was established in a dairy cattle farm. BMs including wither height (WH), hip height (HH), body length (BL), hip width (HW), plus the LWs of cows were first determined manually, by direct measurement. Then the digital photos of cows were taken from different directions synchronously and analyzed by IA software to calculate WH, HH, BL and HW of each cow. After comparing the BMs obtained by IA with the manual measurements, the accuracy was determined as 97.72% for WH, 98.00% for HH, 97.89% for BL and 95.25% for HW. The LW estimation using BMs was then performed by the aid of the regression equations, and the correlation coefficient between the estimated and real (manual) LW values obtained by weighing was calculated as 0.9787, which indicates the IA method is appropriate for LW estimation of Holstein cows. © 2011 Elsevier B.V.
Yazarlar (3)
1
Şakir Taşdemir
2
Abdullah Ürkmez
3
Şeref Inal
Anahtar Kelimeler
Body measurements
Digital image analysis
Live weight
Regression
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
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Scimago Dergi (ISSN Eşleşmesi)
Computers and Electronics in Agriculture
Q1
SJR Skoru2,165
H-Index209
YayıncıElsevier B.V.
ÜlkeNetherlands
Agronomy and Crop Science (Q1)
Animal Science and Zoology (Q1)
Computer Science Applications (Q1)
Forestry (Q1)
Horticulture (Q1)
Metrikler
143
Atıf
3
Yazar
4
Anahtar Kelime