| Wheat yield prediction using machine learning and advanced sensing techniques XE Pantazi, D Moshou, T Alexandridis, RL Whetton, AM Mouazen Computers and electronics in agriculture 121, 57-65, 2016 | 557 | 2016 |
| Machine learning based prediction of soil total nitrogen, organic carbon and moisture content by using VIS-NIR spectroscopy A Morellos, XE Pantazi, D Moshou, T Alexandridis, R Whetton, G Tziotzios, ... Biosystems Engineering 152, 104-116, 2016 | 448 | 2016 |
| Automated leaf disease detection in different crop species through image features analysis and One Class Classifiers XE Pantazi, D Moshou, AA Tamouridou Computers and electronics in agriculture 156, 96-104, 2019 | 311 | 2019 |
| Active learning system for weed species recognition based on hyperspectral sensing XE Pantazi, D Moshou, C Bravo Biosystems Engineering 146, 193-202, 2016 | 166 | 2016 |
| A machine learning approach for the condition monitoring of rotating machinery D Kateris, D Moshou, XE Pantazi, I Gravalos, N Sawalhi, S Loutridis Journal of Mechanical Science and Technology 28, 61-71, 2014 | 101 | 2014 |
| Water stress detection based on optical multisensor fusion with a least squares support vector machine classifier D Moshou, XE Pantazi, D Kateris, I Gravalos Biosystems Engineering 117, 15-22, 2014 | 95 | 2014 |
| Detection of biotic and abiotic stresses in crops by using hierarchical self organizing classifiers XE Pantazi, D Moshou, R Oberti, J West, AM Mouazen, D Bochtis Precision agriculture 18, 383-393, 2017 | 74 | 2017 |
| Detection of Silybum marianum infection with Microbotryum silybum using VNIR field spectroscopy XE Pantazi, AA Tamouridou, TK Alexandridis, AL Lagopodi, G Kontouris, ... Computers and Electronics in Agriculture 137, 130-137, 2017 | 57 | 2017 |
| Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images TK Alexandridis, AA Tamouridou, XE Pantazi, AL Lagopodi, J Kashefi, ... Sensors 17 (9), 2007, 2017 | 53 | 2017 |
| Evaluation of UAV imagery for mapping Silybum marianum weed patches AA Tamouridou, TK Alexandridis, XE Pantazi, AL Lagopodi, J Kashefi, ... International journal of remote sensing 38 (8-10), 2246-2259, 2017 | 53 | 2017 |
| Application of multilayer perceptron with automatic relevance determination on weed mapping using UAV multispectral imagery AA Tamouridou, TK Alexandridis, XE Pantazi, AL Lagopodi, J Kashefi, ... Sensors 17 (10), 2307, 2017 | 40 | 2017 |
| Intelligent data mining and fusion systems in agriculture XE Pantazi, D Moshou, D Bochtis Academic Press, 2019 | 35 | 2019 |
| Leaf disease recognition in vine plants based on local binary patterns and one class support vector machines XE Pantazi, D Moshou, AA Tamouridou, S Kasderidis Artificial Intelligence Applications and Innovations: 12th IFIP WG 12.5 …, 2016 | 27 | 2016 |
| Artificial intelligence in agriculture XE Pantazi, D Moshou, D Bochtis Intelligent data mining and fusion systems in agriculture, 17-101, 2020 | 25 | 2020 |
| Non-destructive early detection and quantitative severity stage classification of Tomato Chlorosis Virus (ToCV) infection in young tomato plants using vis–NIR Spectroscopy A Morellos, G Tziotzios, C Orfanidou, XE Pantazi, C Sarantaris, ... Remote Sensing 12 (12), 1920, 2020 | 24 | 2020 |
| Data Fusion of Proximal Soil Sensing and Remote Crop Sensing for the Delineation of Management Zones in Arable Crop Precision Farming. XE Pantazi, D Moshou, AM Mouazen, T Alexandridis, B Kuang HAICTA, 765-776, 2015 | 23 | 2015 |
| Automatic detection of surface-water bodies from Sentinel-1 images for effective mosquito larvae control G Ovakoglou, I Cherif, TK Alexandridis, XE Pantazi, AA Tamouridou, ... Journal of Applied Remote Sensing 15 (1), 014507-014507, 2021 | 20 | 2021 |
| Crop and weed species recognition based on hyperspectral sensing and active learning D Moshou, D Kateris, XE Pantazi, I Gravalos Precision agriculture'13, 555-561, 2013 | 20 | 2013 |
| Spectral identification of disease in weeds using multilayer perceptron with automatic relevance determination AA Tamouridou, XE Pantazi, T Alexandridis, A Lagopodi, G Kontouris, ... Sensors 18 (9), 2770, 2018 | 16 | 2018 |
| Comparison of deep neural networks in detecting field grapevine diseases using transfer learning A Morellos, XE Pantazi, C Paraskevas, D Moshou Remote Sensing 14 (18), 4648, 2022 | 12 | 2022 |
