Hash based manifold learning technique to generating random fields for image segmentation

Author:

Pemula Rambabu,Naga Raju C.

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Reference34 articles.

1. Rambabu, P., Nagaraju, C.: The optimal thresholding technique for image segmentation using fuzzy otsu method. Int. J. Appl. Eng. Res. 10(13), 33842–33846 (2015)

2. Rambabu, P., Nagaraju, C.: Generation of random fields for object recognization using binarization technique. Int. J. Emerg. Trends Technol. Comput. Sci. 4(5(2)), 8–15 (2015)

3. Chen, Y.-T., Liu, X., Yang, M.-H.: Multi-instance object segmentation with occlusion handling. In: CVPR (2015)

4. Hoiem, D., Efros, A., Hebert, M.: Recovering occlusion boundaries from a single image. In: ICCV (2007)

5. Cordes, K., Scheuermann, B., Rosenhahn, B., Ostermann, J.: Foreground segmentation from occlusions using structure and motion recovery. In: Csurka, G., Kraus, M., Laramee, R.S., Richard, P., Braz, J. (eds.) Computer vision, imaging and computer graphics. Theory and application. Communications in computer and information science, vol. 359, pp. 340–353. Springer, Berlin (2013)

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1. Generation of Random Fields for Image Segmentation Techniques: A Review;International Journal of Image and Graphics;2022-04-13

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