| 图像分类问题的几种深度学习策略 |
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| 引用本文： | 李建伟.图像分类问题的几种深度学习策略[J].数字通信世界,2022(1). |
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| 作者姓名： | 李建伟 |
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| 作者单位： | 北京工业大学信息学部电子科学与技术学院 |
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| 摘 要： | 针对图像分类学习不够深入的问题,提出图像分类问题的几种深度学习策略研究。通过分析当前主流的主动深度学习图像、多标签图像和多尺度网络图像三种深度学习方法的工作原理和存在的优势与不足,探讨图像分类问题的优化学习策略。随后采用图像分类问题的几种深度学习策略实验的方式加以对比,实验结果表明,参数共享的深度学习图像分类方法不仅提高了预测速度,而且还能确保模型的准确性。
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| 关 键 词： | 图像分类 分类方法 深度学习 学习策略 |
Several Deep Learning Strategies for Image Classification |
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| LI Jianwei.Several Deep Learning Strategies for Image Classification[J].Digital Communication World,2022(1). |
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| Authors: | LI Jianwei |
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| Affiliation: | (School of Electronic Science and technology,Department of Information Science,Beijing University of Technology,Beijing 100124,China) |
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| Abstract: | Aiming at the problem that image classification learning is not deep enough,several deep learning strategies for image classification are proposed.By analyzing the working principle,advantages and disadvantages of three mainstream deep learning methods:active deep learning image,multi label image and multi-scale network image,this paper discusses the optimal learning strategy of image classification.Then,several deep learning strategies for image classification are compared.The experimental results show that the parameter sharing deep learning image classification method not only improves the prediction speed,but also ensures the accuracy of the model. |
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| Keywords: | image classification classification method deep learning learning strategy |
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