Assistant Professor (tenure track: RTD-B)
Angelo Genovese is a member of the Industrial, Environmental, and Biometric Informatics Laboratory (IEBIL) at the Università degli Studi di Milano, Italy. He was a Visiting Researcher at the University of Toronto, ON, Canada from June 2017 to August 2017 and from December 2019 to March 2020. Since 2019 he is Assistant Professor at Università degli Studi di Milano, Italy, Department of Computer Science.
His research interests include signal and image processing, three-dimensional reconstruction, computational intelligence technologies, and design methodologies and algorithms for self-adapting systems, applied to industrial and environmental monitoring systems and biometric recognition. In the biometrics field, his focuses are on highly usable touch-based and touchless fingerprint and palmprint recognition, as well as recognition based on soft biometric traits.
Field of Expertise
Signal and image processing, three-dimensional reconstruction, computational intelligence, industrial and environmental monitoring, biometric recognition.
- R. Donida Labati, A. Genovese, E. Muñoz, V. Piuri, and F. Scotti, “Applications of computational intelligence in industrial and environmental scenarios”, in Learning Systems: from Theory to Practice, ser. Studies in Computational Intelligence, V. Sgurev, V. Piuri, and V. Jotsov (eds.), vol. 756, Springer International Publishing, Cham, 2018, pp. 29-46. ISBN: 978-3-319-75180-1.
- R. Donida Labati, A. Genovese, E. Muñoz, V. Piuri, F. Scotti, and G. Sforza, “Computational intelligence for biometric applications: a survey”, in International Journal of Computing, vol. 15, no. 1, 2016, pp. 40-49. ISSN: 2312-5381.
- A. Anand, R. Donida Labati, A. Genovese, E. Muñoz, V. Piuri, and F. Scotti, “Age estimation based on face images and pre-trained Convolutional Neural Networks”, in Proc. of the 2017 IEEE Symp. on Computational Intelligence for Security and Defense Applications (CISDA 2017), Honolulu, HI, USA, November 27-30, 2017, pp. 1-7. ISBN: 978-1-5386-2726-6.
- Source code for the 2017 IEEE SSCI-CISDA paper “Age estimation based on face images and pre-trained Convolutional Neural Networks”
Introduction to Matlab