A. Barbu, G.Gramajo. Face Detection Using a 3D Model on Face Keypoints. (arxiv)
J. Anaya, A. Barbu. RENOIR - A Benchmark Dataset for Real Noise Reduction Evaluation. (pdf)
A. Barbu, Y. She, L. Ding, G. Gramajo. Feature Selection with Annealing for Big Data Learning. (arxiv)
A. Barbu, T.F. Wu, Y. N. Wu. Learning Mixtures of Bernoulli Templates by Two-Round EM with Performance Guarantee. Accepted in Electronic Journal of Statistics (arxiv)
L. Ding, A. Barbu. Scalable Subspace Clustering with Application to Motion Segmentation. Current Trends in Bayesian Methodology with Applications. S.K. Upadhyay. D.K. Dey, U. Singh, A. Loganathan, Editors. Chapman&Hall/CRC Press. 2014 (pdf)
A. Barbu, M. Pavlovskaia, S.C. Zhu. Rates for Inductive Learning of Compositional Models. AAAI Workshop Replearn 2013 (pdf)
A. Barbu. Multi-Path Marginal Space Learning for Object Detection. Academic Press Library in Signal Processing: Volume 4: Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing. pp 271–291, 2013 (pdf)
A. Barbu. Hierarchical Object Parsing from Structured Noisy Point Clouds. IEEE PAMI, 35, No. 7, 1649–1659, 2013. (pdf, arxiv, slides)
L. Ding, A. Barbu, A. Meyer-Baese. Learning a Quality-Based Ranking for Feature Point Trajectories. ACCV 2012 (pdf)
L. Ding, A. Barbu, A. Meyer-Baese. Motion Segmentation by Velocity Clustering with Estimation of Subspace Dimension. ACCV Workshop DTCE 2012 (pdf)
A. Barbu, N. Lay. An Introduction to Artificial Prediction Markets for Classification. Journal of Machine Learning Research, 13, 2177–2204, 2012. (pdf)
A. Barbu, M. Suehling, X. Xu, D. Liu, S. K. Zhou, D. Comaniciu. Automatic Detection and Segmentation of Lymph Nodes from CT Data. IEEE Trans Medical Imaging, 31, No. 2, 240–250, 2012.(pdf)
W. Wu, T. Chen , A. Barbu, P. Wang, N. Strobel, S. Zhou, D. Comaniciu. Learning-based Hypothesis Fusion for Robust Catheter Tracking in 2D X-ray Fluoroscopy. CVPR 2011 (pdf)
F. Bunea, A. Tsybakov, M. Wegkamp and A.Barbu. SPADES and mixture models. Annals of Statistics 38, No. 4, 2525–2558, 2010.(pdf)
F. Bunea and A.Barbu. Dimension reduction and variable selection in case control studies via regularized likelihood optimization. Electronic Journal of Statistics, 3, 2009. (pdf)
A. Barbu. Training an Active Random Field for Real-Time Image Denoising. IEEE Trans. Image Processing, 18, November 2009. (pdf, ppt)
S. Seifert, A. Barbu, S. Zhou, D. Liu, J. Feulner, M. Huber, M. Suehling, A. Cavallaro, D. Comaniciu. Hierarchical parsing and semantic navigation of full body CT data. SPIE Medical Imaging, 2009 (pdf)
Y. Zheng, A. Barbu, B. Georgescu, M. Scheuering and D. Comaniciu. Four-Chamber Heart Modeling and Automatic Segmentation
for 3D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features. IEEE Trans Medical Imaging, November 2008. (pdf)
L. Lu, A. Barbu, M. Wolf, J. Liang, M. Salganicoff, D. Comaniciu. Accurate Polyp Segmentation for 3D CT Colonography Using Multi-Staged Probabilistic Binary Learning and Compositional Model. CVPR 2008.(pdf)
A. Barbu, V. Athitsos, B. Georgescu, S. Boehm, P. Durlak, D. Comaniciu. Hierarchical Learning of Curves: Application to Guidewire Localization in Fluoroscopy. CVPR 2007 (pdf)
A. Barbu, S.C. Zhu. Generalizing Swendsen-Wang for Image Analysis. J. Comp. Graph. Stat. 16, No 4, 2007 (pdf)
A. Barbu, S.C. Zhu. Generalizing Swendsen-Wang to sampling arbitrary posterior probabilities, PAMI, 27, August 2005 (pdf)
A. Barbu, S.C. Zhu. Multigrid and Multi-level Swendsen-Wang Cuts for Hierarchic Graph Partition, CVPR 2004 (pdf)