Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey

作者：

Highlights：

• Gives taxonomy and survey of the evolution of CNN based image segmentation.

• Explores elaborately some CNN based popular state-of-the-art segmentation models.

• Compares training details of those models to have a clear view of hyper-parameter tuning.

• Compares the performance metrics of those state-of-the-art models on different datasets.

摘要

•Gives taxonomy and survey of the evolution of CNN based image segmentation.•Explores elaborately some CNN based popular state-of-the-art segmentation models.•Compares training details of those models to have a clear view of hyper-parameter tuning.•Compares the performance metrics of those state-of-the-art models on different datasets.

论文关键词：Convolutional neural network,Deep learning,Semantic segmentation,Instance segmentation,Panoptic segmentation,Survey

论文评审过程：Received 29 February 2020, Revised 15 May 2020, Accepted 21 May 2020, Available online 26 May 2020, Version of Record 28 May 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.106062