AdaBoost is a practical method of real-time face detection, but abides by a crucial problem of overfitting for the big number of features used in a trained classifier due to the ...
In this work we improve top-down min-cut placers in the context of timing closure. Using the concept of boosting factors, we adjust net weights according to net spans, so as to re...
In this paper, we propose a novel multi-class graph boosting algorithm to recognize different visual objects. The proposed method treats subgraph as feature to construct base clas...
Bang Zhang, Getian Ye, Yang Wang 0002, Wei Wang, J...
This paper presents a novel feature-matching based approach for rigid object tracking. The proposed method models the tracking problem as discovering the affine transforms of obje...
Weiyu Zhu, Song Wang, Ruei-Sung Lin, Stephen E. Le...
Several model-checker based methods to automated test-case generation have been proposed recently. The performance and applicability largely depends on the complexity of the model...
Gordon Fraser, Bernhard K. Aichernig, Franz Wotawa