Semantic segmentation based on DeepLabV3+ and superpixel optimization

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Cite
REN Feng-lei 任凤雷, et al. “Semantic Segmentation Based on DeepLabV3+ and Superpixel Optimization”. Optics and Precision Engineering, vol. 27, no. 12, 2019, pp. 2722-9, https://doi.org/10.3788/ope.20192712.2722.
REN Feng-lei 任., HE Xin 何. 昕., WEI Zhong-hui 魏., L You 吕. 游., & LI Mu-yu 李. (2019). Semantic segmentation based on DeepLabV3+ and superpixel optimization. Optics and Precision Engineering, 27(12), 2722-2729. https://doi.org/10.3788/ope.20192712.2722
REN Feng-lei 任凤雷, HE Xin 何 昕, WEI Zhong-hui 魏仲慧, L You 吕 游, and LI Mu-yu 李沐雨. “Semantic Segmentation Based on DeepLabV3+ and Superpixel Optimization”. Optics and Precision Engineering 27, no. 12 (2019): 2722-29. https://doi.org/10.3788/ope.20192712.2722.
REN Feng-lei 任, HE Xin 何昕, WEI Zhong-hui 魏, L You 吕游, LI Mu-yu 李. Semantic segmentation based on DeepLabV3+ and superpixel optimization. Optics and Precision Engineering. 2019;27(12):2722-9.
Citations
Title Journal Journal Categories Citations Publication Date
Application of Optimized Convolution Neural Network Model in Mural Segmentation

 Applied Computational Intelligence and Soft Computing
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 1 2022
A Novel Squeeze-and-Excitation W-Net for 2D and 3D Building Change Detection with Multi-Source and Multi-Feature Remote Sensing Data

 Remote Sensing
  • Science
  • Geography. Anthropology. Recreation: Environmental sciences
  • Science: Geology
  • Geography. Anthropology. Recreation: Geography (General)
  • Technology: Photography
  • Science: Geology
  • Science: Geology
 25 2021
Citations Analysis
Category Category Repetition
Science1
Geography. Anthropology. Recreation: Environmental sciences1
Science: Geology1
Geography. Anthropology. Recreation: Geography (General)1
Technology: Photography1
Science: Mathematics: Instruments and machines: Electronic computers. Computer science1
The category Science 1 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled A Novel Squeeze-and-Excitation W-Net for 2D and 3D Building Change Detection with Multi-Source and Multi-Feature Remote Sensing Data and was published in 2021. The most recent citation comes from a 2022 study titled Application of Optimized Convolution Neural Network Model in Mural Segmentation. This article reached its peak citation in 2022, with 1 citations. It has been cited in 2 different journals, 100% of which are open access. Among related journals, the Applied Computational Intelligence and Soft Computing cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year