Review the state-of-the-art technologies of semantic segmentation based on deep learning
By Yuji Mo, Y. Wu, Xinneng Yang, Feilin Liu, Yujun Liao. Neurocomputing, 2022
592 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/4b35aa1dadee26439af1b5965aafd93e8cec2086
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Bo Xu
- Shuang Xu
- Jing Shi
- Bidyut Baran Chaudhuri
- Satish Kumar Singh
- Xiuyi Chen
- Shiv Ram Dubey
- Feilong Chen
In Computer Vision and Pattern Recognition
- Bidyut Baran Chaudhuri
- Satish Kumar Singh
- Jing Shi
- Bo Xu
- Shuang Xu
- Xiuyi Chen
- Shiv Ram Dubey
- Feilong Chen
Citations in the corpus
- VLP: A Survey on Vision-language Pre-training (2022, background): “In addition, there are some iamge-related downstream tasks for evaluating the image-text pre-training models, including semantic segmentation [101, 102], and object detection [103, 104].”
- Activation functions in deep learning: A comprehensive survey and benchmark (2021, background): “In recent years, deep learning has shown a tremondous growth to solve the challenging problems such as object detection [1], semantic segmentation [2], person re-identification [3], image retrieval [4], anomaly detection [5], skin disease diagnosis [6], and many more.”