The following publications are possibly variants of this publication:
- Trainable COSFIRE Filters for Keypoint Detection and Pattern RecognitionGeorge Azzopardi, Nicolai Azzopardi. pami, 35(2):490-503, 2013. [doi]
- Recognition of Architectural and Electrical Symbols by COSFIRE Filters with InhibitionJiapan Guo, Chenyu Shi, George Azzopardi, Nicolai Petkov. caip 2015: 348-358 [doi]
- Place and Object Recognition by CNN-Based COSFIRE FiltersManuel Lopez-Antequera, Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov. access, 7:66157-66166, 2019. [doi]
- Color-blob-based COSFIRE filters for object recognitionBaris Gecer, George Azzopardi, Nicolai Petkov. ivc, 57:165-174, 2017. [doi]
- A Shape Descriptor Based on Trainable COSFIRE Filters for the Recognition of Handwritten DigitsGeorge Azzopardi, Nicolai Petkov. caip 2013: 9-16 [doi]
- Gender recognition from face images with trainable COSFIRE filtersGeorge Azzopardi, Antonio Greco, Mario Vento. avss 2016: 235-241 [doi]
- Automatic detection of vascular bifurcations in segmented retinal images using trainable COSFIRE filtersGeorge Azzopardi, Nicolai Petkov. prl, 34(8):922-933, 2013. [doi]
- u-serrated patterns in direct immunofluorescence images of autoimmune bullous diseases by inhibition-augmented COSFIRE filtersChenyu Shi, Joost M. Meijer, Jiapan Guo, George Azzopardi, Gilles F. H. Diercksr, Enno Schmidt, Detlef Zillikens, Marcel F. Jonkman, Nicolai Petkov. ijmi, 122:27-36, 2019. [doi]
- Increased generalization capability of trainable COSFIRE filters with application to machine visionGeorge Azzopardi, Laura Fernández-Robles, Enrique Alegre, Nicolai Petkov. icpr 2016: 3356-3361 [doi]
- Trainable COSFIRE filters for vessel delineation with application to retinal imagesGeorge Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov. mia, 19(1):46-57, 2015. [doi]