Sajad Sabzi
Sajad Sabzi
Verified email at uma.ac.ir
Title
Cited by
Cited by
Year
A fast and accurate expert system for weed identification in potato crops using metaheuristic algorithms
S Sabzi, Y Abbaspour-Gilandeh, G García-Mateos
Computers in Industry 98, 80-89, 2018
472018
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
342013
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
312018
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
252017
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
162019
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
152018
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
122019
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
122018
The use of soft computing to classification of some weeds based on video processing
S Sabzi, Y Abbaspour-Gilandeh, H Javadikia
Applied Soft Computing 56, 107-123, 2017
122017
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
112020
Segmentation of apples in aerial images under sixteen different lighting conditions using color and texture for optimal irrigation
S Sabzi, Y Abbaspour-Gilandeh, G García-Mateos, A Ruiz-Canales, ...
Water 10 (11), 1634, 2018
112018
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
102020
Exploring the best model for sorting blood orange using ANFIS method
S Sabzi, P Javadikia, H Rabbani, A Adelkhani, L Naderloo
Agricultural Engineering International: CIGR Journal 15 (4), 213-219, 2013
102013
Automatic classification of chickpea varieties using computer vision techniques
R Pourdarbani, S Sabzi, VM García-Amicis, G García-Mateos, ...
Agronomy 9 (11), 672, 2019
82019
Automatic Grading of Emperor Apples Based on Image Processing and
S Sabzi, Y Abbaspour-Gilandeh, Y ABBASPOUR-GILANDEH, ...
Journal of Agricultural Sciences 21 (3), 326-336, 2015
82015
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
72020
The use of the combination of texture, color and intensity transformation features for segmentation in the outdoors with emphasis on video processing
S Sabzi, Y Abbaspour-Gilandeh, JL Hernandez-Hernandez, ...
Agriculture 9 (5), 104, 2019
72019
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
62020
Non-intrusive image processing Thompson orange grading methods
S Sabzi, Y Abbaspour-Gilandeh, JI Arribas
2017 56th FITCE Congress, 35-39, 2017
62017
Designing a fruit identification algorithm in orchard conditions to develop robots using video processing and majority voting based on hybrid artificial neural network
S Sabzi, R Pourdarbani, D Kalantari, T Panagopoulos
Applied Sciences 10 (1), 383, 2020
52020
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Articles 1–20