article · 2014

Object Detection

Yuee Liu, Jinglan Zhang, Dian Tjondronegoro, Shlomo Geva, Zhengrong Li

Cited by 0Abstract and details only

Abstract

Semantic object detection is one of the most important and challenging problems in image analysis. Segmentation is an optimal approach to detect salient objects, but often fails to generate meaningful regions due to over-segmentation. This paper presents an improved semantic segmentation approach which is based on JSEG algorithm and utilizes multiple region merging criteria. The experimental results demonstrate that the proposed algorithm is encouraging and effective in salient object detection.

Cite this paper

APA 7

Liu, Y., Zhang, J., Tjondronegoro, D., Geva, S., & Li, Z. (2014). Object Detection.

MLA 9

Liu, Yuee, et al. “Object Detection.” 2014.

Chicago

Liu, Yuee, Jinglan Zhang, Dian Tjondronegoro, Shlomo Geva, and Zhengrong Li. 2014. “Object Detection.”

Harvard

Liu, Y. et al. (2014) ‘Object Detection’.

BibTeX

@article{liu2014object,
  title = {{Object Detection}},
  author = {Liu, Yuee and Zhang, Jinglan and Tjondronegoro, Dian and Geva, Shlomo and Li, Zhengrong},
  year = {2014}
}

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