ScaleNet_ a convolutional network to extract multi-scale and fine-grained visual features | |
Zhang Jinpeng1,2,3,4; Zhang Jinming5; Hu Guyue1,2; Cheng Yang1,2; Yu Shan1,2,3,4 | |
发表期刊 | IEEE Access |
ISSN | 2169-3536 |
2019-10 | |
期号 | 7页码:147560-147570 |
摘要 | Many convolutional neural networks have been proposed for image classification in recent years. Most tend to decrease the plane size of feature maps stage-by-stage, such that the feature maps generated within each stage show the same plane size. This concept governs the design of most classification networks. However, it can also lead to semantic deficiency of high-resolution feature maps as they are always placed in the shallow layers of a network. Here, we propose a novel network architecture, named ScaleNet, which consists of stacked convolution-deconvolution blocks and a multipath residual structure. Unlike most current networks, ScaleNet extracts image features by a cascaded deconstruction-reconstruction process. It can generate scale-variable feature maps within each block and stage, thereby realizing multiscale feature extraction at any depth of the network. Based on the CIFAR-10, CIFAR-100, and ImageNet datasets, ScaleNet demonstrated competitive classification performance compared to state-of-the-art ResNet. In addition, ScaleNet exhibited a powerful ability to capture strong semantic and fine-grained features on its high-resolution feature maps. The code is available at \url{https://github.com/zhjpqq/scalenet}. |
关键词 | Image Classification Convolutional Neural Networks Resnet Deconvolution |
收录类别 | SCI |
语种 | 英语 |
七大方向——子方向分类 | 类脑模型与计算 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/28345 |
专题 | 脑网络组研究 |
作者单位 | 1.Chinese Acad Sci, Brainnetome Ctr, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Zhang Jinpeng,Zhang Jinming,Hu Guyue,et al. ScaleNet_ a convolutional network to extract multi-scale and fine-grained visual features[J]. IEEE Access,2019(7):147560-147570. |
APA | Zhang Jinpeng,Zhang Jinming,Hu Guyue,Cheng Yang,&Yu Shan.(2019).ScaleNet_ a convolutional network to extract multi-scale and fine-grained visual features.IEEE Access(7),147560-147570. |
MLA | Zhang Jinpeng,et al."ScaleNet_ a convolutional network to extract multi-scale and fine-grained visual features".IEEE Access .7(2019):147560-147570. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
ScaleNet_ a convolut(1764KB) | 期刊 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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