Image categorization with resource constraints： introduction, challenges and advances

As one of the most classic fields in computer vision, image categorization has attracted widespread interests. Numerous algorithms have been proposed in the community, and many of them have advanced the state-of-the-art. However, most existing algorithms are designed without consideration for the su...

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Bibliographic Details
Published in:Frontiers of Computer Science 2017-02, Vol.11 (1), p.13-26
Main Authors: LUO, Jian-Hao, ZHOU, Wang, WU, Jianxin
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Artificial neural networks
Classification
Computer Science
Computer vision
Constraints
deep neural networks
Energy consumption
image categorization
Image retrieval
large scale classification
Neural networks
resource constraints
Review Article
Support vector machines
图像分类
研究开发
神经网络
算法
计算机视觉
计算资源
资源受限
资源约束
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Summary:As one of the most classic fields in computer vision, image categorization has attracted widespread interests. Numerous algorithms have been proposed in the community, and many of them have advanced the state-of-the-art. However, most existing algorithms are designed without consideration for the supply of computing resources. Therefore, when dealing with resource constrained tasks, these algorithms will fail to give satisfactory results. In this paper, we provide a comprehensive and in-depth introduction of recent developments of the research in image categorization with resource constraints. While a large portion is based on our own work, we will also give a brief description of other elegant algorithms. Furthermore, we make an investigation into the recent developments of deep neural networks, with a focus on resource constrained deep nets.
ISSN:2095-2228
2095-2236
DOI:10.1007/s11704-016-5514-6