Publikationen in Zusammenarbeit mit Forschern von University of Mohaghegh Ardabili (22)

2024

  1. A stereoscopic video computer vision system for weed discrimination in rice field under both natural and controlled light conditions by machine learning

    Measurement: Journal of the International Measurement Confederation, Vol. 237

  2. Automatic non-destructive estimation of polyphenol oxidase and peroxidase enzyme activity levels in three bell pepper varieties by Vis/NIR spectroscopy imaging data based on machine learning methods

    Chemometrics and Intelligent Laboratory Systems, Vol. 250

2023

  1. Examination of Lemon Bruising Using Different CNN-Based Classifiers and Local Spectral-Spatial Hyperspectral Imaging

    Algorithms, Vol. 16, Núm. 2

  2. From Harvest to Market: Non-Destructive Bruise Detection in Kiwifruit Using Convolutional Neural Networks and Hyperspectral Imaging

    Horticulturae, Vol. 9, Núm. 8

2022

  1. Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants

    Journal of Near Infrared Spectroscopy, Vol. 30, Núm. 4, pp. 197-207

2021

  1. Estimation of nitrogen content in cucumber plant (Cucumis sativus L.) leaves using hyperspectral imaging data with neural network and partial least squares regressions

    Chemometrics and Intelligent Laboratory Systems, Vol. 217

  2. Identification of internal defects in potato using spectroscopy and computational intelligence based on majority voting techniques

    Foods, Vol. 10, Núm. 5

  3. Nondestructive estimation of three apple fruit properties at various ripening levels with optimal Vis-NIR spectral wavelength regression data

    Heliyon, Vol. 7, Núm. 9

  4. Nondestructive nitrogen content estimation in tomato plant leaves by Vis-NIR hyperspectral imaging and regression data models

    Applied Optics, Vol. 60, Núm. 30, pp. 9560-9569

2020

  1. A computer vision system based on majority-voting ensemble neural network for the automatic classification of three chickpea varieties

    Foods, Vol. 9, Núm. 2

  2. A computer vision system for the automatic classification of five varieties of tree leaf images

    Computers, Vol. 9, Núm. 1

  3. A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value

    Measurement: Journal of the International Measurement Confederation, Vol. 152

  4. An automatic visible-range video weed detection, segmentation and classification prototype in potato field

    Heliyon, Vol. 6, Núm. 5

  5. 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

    Biosystems Engineering, Vol. 195, pp. 136-151

  6. Non-destructive estimation of chlorophyll a content in red delicious apple cultivar based on spectral and color data

    Tarim Bilimleri Dergisi, Vol. 26, Núm. 3, pp. 339-348

  7. Non-destructive visible and short-wave near-infrared spectroscopic data estimation of various physicochemical properties of Fuji apple (Malus pumila) fruits at different maturation stages

    Chemometrics and Intelligent Laboratory Systems, Vol. 206

  8. Weed classification for site-specific weed management using an automated stereo computer-vision machine-learning system in rice fields

    Plants, Vol. 9, Núm. 5

2019

  1. A video image segmentation system for the fruit-trees in multi-stage outdoors orchard under natural conditions

    Tarim Bilimleri Dergisi, Vol. 25, Núm. 4, pp. 427-439

  2. An automatic non-destructive method for the classification of the ripeness stage of red delicious apples in orchards using aerial video

    Agronomy, Vol. 9, Núm. 2

2018

  1. A visible-range computer-vision system for automated, non-intrusive assessment of the pH value in Thomson oranges

    Computers in Industry, Vol. 99, pp. 69-82