Int. J. Simul. Multidisci. Des. Optim.
Volume 10, 2019
|Number of page(s)||9|
|Published online||23 September 2019|
- N. Dalal, B. Triggs, Histograms of Oriented Gradients for Human Detection, in: Conference on Computer Vision and Pattern Recognition , 2005 [Google Scholar]
- P. Dollàr, Z. Tu, P. Perona, S. Belongie, Integral channel features, in: Proceedings of the British Machine Vision Conference , 2009, pp. 91.1–91.11 [Google Scholar]
- P. Dollaár, R. Appel, S. Belongie, P. Perona, Fast feature pyramids for object detection, in: Transactions on pattern analysis and machine intelligence (TPAMI) , 2014 [Google Scholar]
- S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: towards real-time object detection with region proposal networks, in: Advances in Neural Information Processing Systems 28 (NIPS) , 2015 [Google Scholar]
- J. Redmon, S. Divvala, R. Girshick, A. Farhadi, You only look once: unified, real-time object detection, Computer Vision and Pattern Recognition , 2016 [Google Scholar]
- L. Zhang, B. Wu, R. Nevatia, I. Systems, L. Angeles, Pedestrian Detection in Infrared Images based on Local Shape Features, in: Computer Vision and Pattern Recognition (CVPR) , 2007 [Google Scholar]
- D. Olmeda, J.M. Armingol, Contrast Invariant Features for Human Detection in Far Infrared Images, in: Intelligent Vehicles Symposium (IV) , 2012 [Google Scholar]
- D. Olmeda, Pedestrian detection in far infrared images, Ph.D. dissertation, 2013 [Google Scholar]
- R. Brehar, C. Vancea, S. Nedevschi, Pedestrian detection in infrared images using aggregated channel features, in: Intelligent Computer Communication and Processing (ICCP) , 2014 [Google Scholar]
- A. Blum, T. Mitchell, Combining labeled and unlabeled data with co-training, in: COmputational Learning Theory (COLT) , 1998 [Google Scholar]
- A. Levin, P. Viola, O.M. Way, Y. Freund, Unsupervised improvement of visual detectors using co-training, in: International Conference on Computer Vision (ICCV) , 2003 [Google Scholar]
- P.M. Roth, C. Leistner, A. Berger, H. Bischof, Multiple instance learning from multiple cameras, in: Conference on Computer Vision and Pattern Recognition Workshop (CVPRW) , 2010 [Google Scholar]
- S.J. Krotosky, M.M. Trivedi, Mutual information based registration of multimodal stereo videos for person tracking, in: Computer Vision and Image Understanding (CVIU), 2007 [Google Scholar]
- J.-Y. Bouguet, Jean-yves bouguet's matlab toolbox for calibrating cameras, 2015, http://www.vision.caltech.edu/bouguetj/calib-doc/ [Google Scholar]
- Z. Shi, T. Wei, M.K. Taghi, Boosted Noise Filters for Identifying Mislabeled Data, Department of Computer Science and Engineering Florida Atlantic University, 2005 [Google Scholar]
- C.L. Zitnick, P. Dollàr, Edge boxes: locating object proposals from edges, in: European Conference on Computer Vision (ECCV) , 2013 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.