Impact Factor:6.549
Scopus Suggested Journal: |
International Journal
of Computer Engineering in Research Trends (IJCERT)
Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary
International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary
ISSN(Online):2349-7084 Submit Paper Check Paper Status Conference Proposal
[1] L. Ladicky, C. Russell, P. Kohli, and P. H. S. Torr, “Graph cut based inference with co-occurrence statistics,” in Proc. Eur. Conf. Comput.Vis., Heraklion, Greece, 2010, pp. 239–253. [2] H. Lu, G. Fang, X. Shao, and X. Li, “Segmenting human from photo images based on a coarse-to-fine scheme,” IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 42, no. 3, pp. 889–899, Jun. 2012. [3] J. Carreira and C. Sminchisescu, “CPMC: Automatic object segmentation using constrained parametric min-cuts,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 7, pp. 1312–1328, Jul. 2012. [4] Y.-L. Hou and G. K. H. Pang, “Multicue-based crowd segmentation using appearance and motion,” IEEE Trans. Syst., Man, Cybern., Syst., vol. 43, no. 2, pp. 356–369, Mar. 2013. [5] X. Yuan, J. Guo, X. Hao, and H. Chen, “Traffic sign detection via graphbased ranking and segmentation algorithms,” IEEE Trans. Syst., Man, Cybern., Syst., vol. 45, no. 12, pp. 1509–1521, Dec. 2015. [6] Y.-T. Chen, X. Liu, and M.-H. Yang, “Multi-instance object segmentation with occlusion handling,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Boston, MA, USA, 2015, pp. 3470–3478. [7] J. Wang and A. L. Yuille, “Semantic part segmentation using compositional model combining shape and appearance,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Boston, MA, USA, 2015, pp. 1788–1797. [8] H. Zhang, J. E. Fritts, and S. A. Goldman, “Image segmentation evaluation: A survey of unsupervised methods,” Comput. Vis. Image Understand., vol. 110, no. 2, pp. 260–280, 2008. [9] G. Csurka and F. Perronnin, “A simple high performance approach to semantic segmentation,” in Proc. Brit. Mach. Vis. Conf., Leeds, U.K., 2008, pp. 1–10. [10] F. Wang, Q. Huang, M. Ovsjanikov, and L. J. Guibas, “Unsupervised multi-class joint image segmentation,” in Proc. IEEE Conf. Comput. Vis.Pattern Recognit., Columbus, OH, USA, 2014, pp. 3142–3149. [11] A. Vezhnevets, V. Ferrari, and J. M. Buhmann, “Weakly supervised semantic segmentation with a multi-image model,” in Proc. IEEE Int.Conf. Comput. Vis., Barcelona, Spain, 2011, pp. 643–650. [12] Y. Liu, J. Liu, Z. Li, J. Tang, and H. Lu, “Weakly-supervised dual clustering for image semantic segmentation,” in Proc. IEEE Conf. Comput.Vis. Pattern Recognit., Portland, OR, USA, 2013, pp. 2075–2082. [13] L. Zhang et al., “Probabilistic graphlet cut: Exploiting spatial structure cue for weakly supervised image segmentation,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Portland, OR, USA, 2013, pp. 1908–1915. [14] K. Zhang, W. Zhang, Y. Zheng, and X. Xue, “Sparse reconstruction for weakly supervised semantic segmentation,” in Proc. Int. Joint Conf.Artif. Intell., Beijing, China, 2013, pp. 1889–1895. [15] L. Zhang et al., “A probabilistic associative model for segmenting weakly supervised images,” IEEE Trans. Image Process., vol. 23, no. 9,pp. 4150–4159, Sep. 2014. [16] P. O. Pinheiro and R. Collobert, “From image-level to pixel-level labeling with convolutional networks,” in Proc. IEEE Conf. Comput. Vis.Pattern Recognit., Boston, MA, USA, 2015, pp. 1713–1721. [17] J. Dai, K. He, and J. Sun, “Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation,” in Proc. IEEE Int. Conf. Comput. Vis., Santiago, Chile, 2015,pp. 1635–1643 [18] Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Susstrunk, SLIC Superpixels, EPFL Technical Report 149300, June 2010. [19] Yi Li, Yanqing Guo, Member, IEEE, Yueying Kao, and Ran He “Image Piece Learning for Weakly Supervised Semantic Segmentation” IEEE transaction on systems, man, and cybernetics: systems, vol. 47, april 2017.
![]() | V6I701.pdf |