Abstract Despite many years of research, obstacle recognition is still a difficult, but very important task. We present a multi-class approach, that extracts from images the Histogram of Oriented Gradients (HOG) based on aspect ratio of Region of Interest (ROI) and use them in a multiclass classification problem. For the learning phase we propose…
The detection of tumors in digital images originated from mammograms can be a challenging task. In this paper we investigate a Computer Aided Diagnosis System based on a Genetic Programming classifier. The performance of the considered classifier is evaluated for five of the image descriptors used in literature and we propose a new approach,…
Despite many years of research, breast cancer detection is still a difficult, but very important problem to be solved. An automatic diagnosis system could establish whether a mammography presents tumours or belongs to a healthy patient and could offer, in this way, a second opinion to a radiologist that tries to establish a diagnosis.…
I.G. Mircea, G. Czibula, M.R. Petrușel, Sex Identification in Archaeological Remains Using Decision Tree Learning, Studia Universitatis Babes-Bolyai, Informatica, 2015, pages 91-103
R. Mocan, L. Diosan, “Obstacle recognition in traffic by adapting the hog descriptor and learning in layers,” Studia Univ. Babes–Bolyai, Informatica, vol. 55, Nr 2, 2015