Challenges and Recent Solutions for Image Segmentation in the Era of Deep Learning

GÖÇERİ E.

9th International Conference on Image Processing Theory, Tools and Applications (IPTA), İstanbul, Turkey, 6 - 09 November 2019 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ipta.2019.8936087
  • City: İstanbul
  • Country: Turkey
  • Keywords: CNN, deep learning, image segmentation, neural networks, transfer learning, NEURAL-NETWORK, CNN, EXTRACTION, MRI
  • Akdeniz University Affiliated: Yes

Abstract

Image segmentation has a key role in computer vision and image processing. Superiority of deep learning based segmentation techniques has been shown in various studies in the literature. However, there are challenging issues affecting performances of these methods. Therefore, in this paper, these challenges that are mostly related to architecture and training of deep neural networks are explained. In addition, the state-of-the-art solutions applied in the literature are presented to help researchers to design proper network architectures according to their problems and to be aware of possible challenging issues and recent solutions.