Dr. Hamed Tavakoli
Abteilung: Agromechatronik
Mitarbeit in Forschungsprogrammen
Arbeitsgebiete
- Sensorbasierte Technologien in der Präzisionslandwirtschaft
- Sensorbasierte Bodencharakterisierung
- Entwurf und Entwicklung von Sensorsystemen zur Überwachung von Pflanzen und Böden
- Optische Spektroskopie
Projekte
Veröffentlichungen
- Tavakoli, H.; Correa Reyes, J.; Vogel, S.; Oertel, M.; Zimne, M.; Heisig, M.; Harder, A.; Wruck, R.; Pätzold, S.; Leenen, M.; Gebbers, R. (2024): The RapidMapper: State-of-the-art in mobile proximal soil sensing based on a novel multi-sensor platform. Computers and Electronics in Agriculture. (November): p. 109443. Online: https://www.sciencedirect.com/science/article/pii/S0168169924008342
- Schmidinger, J.; Barkov, V.; Tavakoli, H.; Correa Reyes, J.; Ostermann, M.; Atzmüller, M.; Gebbers, R.; Vogel, S. (2024): Which and how many soil sensors are ideal to predict key soil properties: A case study with seven sensors. Geoderma. (October): p. 117017. Online: https://doi.org/10.1016/j.geoderma.2024.117017
- Tavakoli, H.; Correa Reyes, J.; Sabetizadeh, M.; Vogel, S. (2023): Predicting key soil properties from Vis-NIR spectra by applying dual-wavelength indices transformations and stacking machine learning approaches. Soil and Tillage Research. (May): p. 105684. Online: https://doi.org/10.1016/j.still.2023.105684
- Alirezazadeh, P.; Rahimi-Ajdadi, F.; Abbaspour-Gilandeh, Y.; Landwehr, N.; Tavakoli, H. (2021): Improved digital image-based assessment of soil aggregate size by applying convolutional neural networks. Computers and Electronics in Agriculture. (December): p. 106499. Online: https://doi.org/10.1016/j.compag.2021.106499
- Tavakoli, H.; Alirezazadeh, P.; Hedayatipour, A.; Banijamali Nasib, A.; Landwehr, N. (2021): Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks. Computers and Electronics in Agriculture. (February): p. 105935. Online: https://doi.org/10.1016/j.compag.2020.105935
- Tavakoli, H.; Mohtasebi, S.; Alimardani, R.; Gebbers, R. (2014): Evaluation of different sensing approaches concerning to nondestructive estimation of leaf area index (LAI) for winter wheat. International Journal on Smart Sensing and Intelligent Systems. (1 March): p. 337-359. Online: http://www.s2is.org/Issues/v7/n1/papers/paper18.pdf
Weitere Veröffentlichungen
Yaghoubi, M. and Tavakoli, H. 2022. Mechanical Design of Machine Elements by Graphical Methods. Springer, Cham, Hardcover ISBN: 978-3-031-04328-4, eBook ISBN: 978-3-031-04329-1, DOI: https://doi.org/10.1007/978-3-031-04329-1.
Lashgari, M., Imanmehr, A. and Tavakoli, H. 2020. Fusion of acoustic sensing and deep learning techniques for apple mealiness detection. Journal of Food Science and Technology, 57, 2233–2240. https://doi.org/10.1007/s13197-020-04259-y
Tavakoli, H. and Gebbers, R. 2019. Assessing Nitrogen and water status of winter wheat using a digital camera. Computers and Electronics in Agriculture, 157: 558‒567.
Tavakoli, H., Mohtasebi, S.S. and Gebbers, R. 2015. An image processing based approach for detection of nitrogen status in winter wheat under mild drought stress. 7th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, 17-20 September 2015; Kavala, Greece.
Gebbers, R., Tavakoli, H. and Herbst, R. 2013. Crop sensor readings in winter wheat as affected by nitrogen and water supply. 9th European Conference on Precision Agriculture, 7-11 July 2013; Lleida, Catalonia, Spain.
Komarizadeh, M.H., Ghazavi, M.A., Alizadeh, M.R., Zareiforush, H., Tavakoli, H. and Masoomi, M. 2011. Power Requirements for Paddy (Oriza sativa L.) Grains Handling with Screw Augers. Applied Engineering in Agriculture (ASABE Publication), 28(1): 73‒78.
Zareiforoush, H., Komarizadeh, M.H., Alizadeh, M.R., Masoumi, M. and Tavakoli, H. 2010. Performance evaluation of screw augers in paddy grains handling. International Agrophysics, 24(4): 389‒391.
Tavakoli, H., Mohtasebi, S.S., Jafari, A. and Nazari Galedar, M. 2009. Some engineering properties of barley straw. Applied Engineering in Agriculture (ASABE Publication), 25(4): 627‒633.