Lightweight and efficient asymmetric network design for real-time semantic segmentation
Author:
Funder
National Key Research and Development Program of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-02437-9.pdf
Reference48 articles.
1. Minaee S, Boykov Y, Porikli F, Plaza A, Kehtarnavaz N (2021) Image segmentation using deep learning. A Survey. IEEE Trans Pattern Anal Mach Intell, https://doi.org/10.1109/TPAMI.2021.3059968
2. Wu J, Jiao J, Yang Q, Zha ZJ (2019) Ground-aware point cloud semantic segmentation for autonomous driving. In: MM 2019 - Proceedings of the 27th ACM international conference on multimedia, pp 971–979
3. Chen C, Wang G (2020) IOSUDA: an unsupervised domain adaptation with input and output space alignment for joint optic disc and cup segmentation. Appl Intell, https://doi.org/10.1007/s10489-020-01956-1
4. Long J, Shelhamer E, Darrell T (2015) Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR), pp 3431–3440
5. Chen LC, Papandreou G, Kokkinos I, Murphy K, Yuille AL (2017) Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans Pattern Anal Mach Intell 40(4):834–848
Cited by 34 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. LMANet: A Lightweight Asymmetric Semantic Segmentation Network Based on Multi-Scale Feature Extraction;Electronics;2024-08-23
2. Omni-scale feature learning for lightweight image dehazing;Applied Intelligence;2024-08-03
3. Exploring Generalizable Distillation for Efficient Medical Image Segmentation;IEEE Journal of Biomedical and Health Informatics;2024-07
4. Multiple Resolutions Detail Enhancement Network for Real-Time Image Semantic Segmentation;IEEE Transactions on Artificial Intelligence;2024-07
5. LACTNet: A Lightweight Real-Time Semantic Segmentation Network Based on an Aggregated Convolutional Neural Network and Transformer;Electronics;2024-06-19
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3