We present a novel boosting algorithm where temporal consistency is addressed in a short-term way. Although temporal correlation of observed data may be an important cue for classi...
Pedro Canotilho Ribeiro, Plinio Moreno, José...
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Abstract--In this paper, a new algorithm for vehicle logo recognition on the basis of an enhanced scale-invariant feature transform (SIFT)-based feature-matching scheme is proposed...
Apostolos P. Psyllos, Christos-Nikolaos Anagnostop...
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...