Publicatii recente
Publicatii recente
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Multiclass classification based on clustering approaches for obstacle recognition in traffic scenes (2016)
Abstract Traffic scene object detection and recognition is extensively researched in the field of roadside assistance. Due to its importance, many methods have been proposed to solve the classification of […]
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Exploring Various Neighborhoods in Cellular Automata for Image Segmentation (2016)
Abstract This paper presents the first results obtained by exploring different neighborhoods in two-dimensional Cellular Automata applied for the difficult task of automatic image segmentation. Numerical experiments have been performed […]
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Investigation of Cellular Automata Neighbourhoods in Image Segmentation (2016)
Abstract Cellular Automata (CA) can be successfully applied to the task of image segmentation. The CA-based GrowCut algorithm is able to perform such a task and we aim to investigate […]
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Support Vector Machine and Boosting based Multiclass Classification for Traffic Scene Obstacles (2016)
Abstract Multiclass classification is an extensively researched topic due to its importance in making the binary classification problems a complex and well tuned system and minimising the running time for […]
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Support vector machine and boosting based Multiclass classification for traffic scene obstacles (2016)
R. Mocan, L. Diosan, “Support vector machine and boosting based Multiclass classification for traffic scene obstacles”, Studia Univ. Babes–Bolyai, Informatica, Vol. 61, Nr 2, 2016
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Multiclass classification based on clustering approaches for obstacle recognition in traffic scenes (2016)
R. Mocan, L. Diosan, “Multiclass classification based on clustering approaches for obstacle recognition in traffic scenes”, 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), 2016, pp. […]
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Pedestrian recognition using a dynamic modality fusion approach
Abstract It was proved that the fusion of information from multi-modality images increases the accuracy of pedestrian recognition systems. One of the best approach so far is to concatenate the […]
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Pedestrian recognition by using a dynamic modality selection approach
Abstract Despite many years of research, pedestrian recognition is still a difficult, but very important task. It was proved that concatenating information from multi-modality images improves the recognition accuracy, but […]
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Descriptors fusion and genetic programming for breast cancer detection (2015)
Abstract 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 […]
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Multi-objective breast cancer classification by using Multi-Expression Programming (2015)
Abstract 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 […]
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