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Sajad Sabzi
Sajad Sabzi
Department of Computer Engineering, Sharif University of Technology, Tehran 11155-1639, Iran
Подтвержден адрес электронной почты в домене sharif.edu
Название
Процитировано
Процитировано
Год
A fast and accurate expert system for weed identification in potato crops using metaheuristic algorithms
S Sabzi, Y Abbaspour-Gilandeh, G Garcia-Mateos
Computers in Industry 98, 80-89, 2018
1352018
Weed classification for site-specific weed management using an automated stereo computer-vision machine-learning system in rice fields
M Dadashzadeh, Y Abbaspour-Gilandeh, T Mesri-Gundoshmian, S Sabzi, ...
Plants 9 (5), 559, 2020
672020
A new approach for visual identification of orange varieties using neural networks and metaheuristic algorithms
S Sabzi, Y Abbaspour-Gilandeh, G García-Mateos
Information processing in agriculture 5 (1), 162-172, 2018
662018
Intelligent detection of citrus fruit pests using machine vision system and convolutional neural network through transfer learning technique
R Hadipour-Rokni, EA Asli-Ardeh, A Jahanbakhshi, S Sabzi
Computers in Biology and Medicine 155, 106611, 2023
652023
An automatic visible-range video weed detection, segmentation and classification prototype in potato field
S Sabzi, Y Abbaspour-Gilandeh, JI Arribas
Heliyon 6 (5), 2020
642020
Machine vision system for the automatic segmentation of plants under different lighting conditions
S Sabzi, Y Abbaspour-Gilandeh, H Javadikia
Biosystems Engineering 161, 157-173, 2017
562017
Automatic non-destructive video estimation of maturation levels in Fuji apple (Malus Malus pumila) fruit in orchard based on colour (Vis) and spectral (NIR) data
R Pourdarbani, S Sabzi, D Kalantari, R Karimzadeh, E Ilbeygi, JI Arribas
Biosystems Engineering 195, 136-151, 2020
542020
A combined method of image processing and artificial neural network for the identification of 13 Iranian rice cultivars
Y Abbaspour-Gilandeh, A Molaee, S Sabzi, N Nabipur, S Shamshirband, ...
Agronomy 10 (1), 117, 2020
512020
Mass modeling of Bam orange with ANFIS and SPSS methods for using in machine vision
S Sabzi, P Javadikia, H Rabani, A Adelkhani
Measurement 46 (9), 3333-3341, 2013
482013
Non-destructive estimation of physicochemical properties and detection of ripeness level of apples using machine vision
S Sabzi, M Nadimi, Y Abbaspour-Gilandeh, J Paliwal
International Journal of Fruit Science 22 (1), 628-645, 2022
432022
Non-destructive visible and short-wave near-infrared spectroscopic data estimation of various physicochemical properties of Fuji apple (Malus pumila) fruits at different …
R Pourdarbani, S Sabzi, D Kalantari, JI Arribas
Chemometrics and Intelligent Laboratory Systems 206, 104147, 2020
412020
Using video processing to classify potato plant and three types of weed using hybrid of artificial neural network and partincle swarm algorithm
S Sabzi, Y Abbaspour-Gilandeh
Measurement 126, 22-36, 2018
402018
A computer vision system based on majority-voting ensemble neural network for the automatic classification of three chickpea varieties
R Pourdarbani, S Sabzi, D Kalantari, JL Hernández-Hernández, JI Arribas
Foods 9 (2), 113, 2020
392020
An automatic non-destructive method for the classification of the ripeness stage of red delicious apples in orchards using aerial video
S Sabzi, Y Abbaspour-Gilandeh, G García-Mateos, A Ruiz-Canales, ...
Agronomy 9 (2), 84, 2019
392019
Estimation of nitrogen content in cucumber plant (Cucumis sativus L.) leaves using hyperspectral imaging data with neural network and partial least squares regressions
S Sabzi, R Pourdarbani, MH Rohban, G García-Mateos, JI Arribas
Chemometrics and Intelligent Laboratory Systems 217, 104404, 2021
382021
Comparison of different classifiers and the majority voting rule for the detection of plum fruits in garden conditions
R Pourdarbani, S Sabzi, M Hernández-Hernández, ...
Remote sensing 11 (21), 2546, 2019
382019
Convolutional neural networks for estimating the ripening state of fuji apples using visible and near-infrared spectroscopy
B Benmouna, G García-Mateos, S Sabzi, R Fernandez-Beltran, ...
Food and Bioprocess Technology 15 (10), 2226-2236, 2022
342022
A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value
S Sabzi, H Javadikia, JI Arribas
Measurement 152, 107298, 2020
302020
Automatic classification of chickpea varieties using computer vision techniques
R Pourdarbani, S Sabzi, VM García-Amicis, G García-Mateos, ...
Agronomy 9 (11), 672, 2019
292019
A visible-range computer-vision system for automated, non-intrusive assessment of the pH value in Thomson oranges
S Sabzi, JI Arribas
Computers in Industry 99, 69-82, 2018
292018
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