Deep learning for image segmentation-a short survey
Year: 2019
Type: preprint
Abstract: Deep learning works as a discrete non-linear mapping function and has achieved great success as a powerful classification tool. However, is deep learning omnipotent? This paper gives a short survey of the accuracy achieved by deep learning so far in image segmentation. Compared to the close to 100% classification accuracy achieved by deep learning, the image segmentation accuracy achieved by deep learning is only about 80%. We analyze the possible reasons why deep learning could not achieve acceptable accuracy in image segmentation and found that deep learning only generates a prediction map and relies on other segmentation methods to complete the segmentation task. In addition, the performance of deep learning is determined by the number of outputs. Consequently, deep learning could not achieve high segmentation accuracy unless the resolution of the image is extremely small.
Source: arXiv (Cornell University)
Author: Zhenzhou Wang
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2948658236