语义分割的卷积神经网络研究进展

Abdelrahman Kaseb, Mahmoud Khaled, Omar Galal
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引用次数: 1

摘要

图像分割是计算机视觉中研究最多的问题之一。使用和实验了人工智能和机器学习中的各种算法和技术。最近,深度学习模型在大多数知名的语义分割数据集上提高了最先进的性能。在这项工作中,我们对语义分割中最新的9种模型和方法进行了全面研究。我们在不同的数据集上对这些模型进行实验并得出结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Convolutional Neural Networks for Semantic Segmentation: A Recent Survey
Image segmentation is one of the most researched problems in computer vision. Various algorithms and techniques in artificial intelligence and machine learning were used and experimented with. Recently deep learning models have improved state-of-the-art performance on most of the well-known semantic segmentation datasets. In this work, we present a comprehensive study of 9 of the most recent models and methods in semantic segmentation. We experiment with these models on different datasets and draw our conclusions.
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