Pendar Alirezazadeh
Abteilung: Agromechatronik
Mitarbeit in Programmbereichen
Arbeitsgebiete
Machine/Deep Learning, Few-Shot Learning, Transformers, Neural Network Loss Functions, Self-attention Mechanism
Projekte
- BETTER-WEEDS – Wissensbasierte Standortanalyse für ein umweltgerechtes Unkrautmanagement im integrierten Pflanzenbau Derzeit erfolgt die Unkrautkontrolle in konventionellen Ackerbausystemen überwiegend durch angepasste Herbizidstrategien. Vor dem Hin…
- weed-AI-seek – Entwicklung eines intelligenten UAV-gestützten Unkrautmonitoringsystems für den selektiven und teilflächenspezifischen Herbizideinsatz Die Zielsetzung des Projekts weed-AI-seek ist es, ein intelligentes echtzeitfähiges Monitoring- und…
Veröffentlichungen
- Alirezazadeh, P.; Schirrmann, M.; Stolzenburg, F. (2023): Improving Deep Learning-based Plant Disease Classification with Attention Mechanism. Gesunde Pflanzen. (1): p. 49-59. Online: https://doi.org/10.1007/s10343-022-00796-y
- 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
- 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
Veröffentlichungen vor ATB-Zugehörigkeit
Alirezazadeh, P., Dornaika, F. and Moujahid, A., 2022. Deep Learning with Discriminative Margin Loss for Cross-Domain Consumer-to-Shop Clothes Retrieval. Sensors, 22(7), p.2660.
Proença, H., Yaghoubi, E. and Alirezazadeh, P., 2020. A Quadruplet Loss for Enforcing Semantically Coherent Embeddings in Multi-Output Classification Problems. IEEE Transactions on Information Forensics and Security, 16, pp.800-811.
Alirezazadeh, P., Yaghoubi, E., Assunção, E., Neves, J.C. and Proença, H., 2019, September. Pose Switch-based Convolutional Neural Network for Clothing Analysis in Visual Surveillance Environment. In 2019 International Conference of the Biometrics Special Interest Group (BIOSIG) (pp. 1-5). IEEE.
Yaghoubi, E., Alirezazadeh, P., Assunção, E., Neves, J.C. and Proençaã, H., 2019, September. Region-based cnns for pedestrian gender recognition in visual surveillance environments. In 2019 International Conference of the Biometrics Special Interest Group (BIOSIG) (pp. 1-5). IEEE.
Alirezazadeh, P., Hejrati, B., Monsef-Esfahani, A. and Fathi, A., 2018. Representation learning-based unsupervised domain adaptation for classification of breast cancer histopathology images. Biocybernetics and Biomedical Engineering, 38(3), pp.671-683.
Alirezazadeh, P., Fathi, A. and Abdali-Mohammadi, F., 2016. Effect of purposeful feature extraction in high-dimensional kinship verification problem. Journal of Computing and Security, 3(3), pp.183-191.
Fathi, A., Alirezazadeh, P. and Abdali-Mohammadi, F., 2016. A new Global-Gabor-Zernike feature descriptor and its application to face recognition. Journal of Visual Communication and Image Representation, 38, pp.65-72.
Alirezazadeh, P., Fathi, A. and Abdali-Mohammadi, F., 2015. A genetic algorithm-based feature selection for kinship verification. IEEE Signal Processing Letters, 22(12), pp.2459-2463.