Folgen
Sajad Sabzi
Sajad Sabzi
Department of Computer Engineering, Sharif University of Technology, Tehran 11155-1639, Iran
Bestätigte E-Mail-Adresse bei sharif.edu
Titel
Zitiert von
Zitiert von
Jahr
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
1202018
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
582020
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
552018
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
512017
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
492020
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
492020
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
462013
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
412020
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
372020
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
352018
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
342023
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
342020
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
342019
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
292022
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
292019
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
282021
Automatic classification of chickpea varieties using computer vision techniques
R Pourdarbani, S Sabzi, VM García-Amicis, G García-Mateos, ...
Agronomy 9 (11), 672, 2019
272019
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
252018
Estimation of different ripening stages of Fuji apples using image processing and spectroscopy based on the majority voting method
R Pourdarbani, S Sabzi, D Kalantari, J Paliwal, B Benmouna, ...
Computers and Electronics in Agriculture 176, 105643, 2020
222020
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
222020
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20