Research for image caption based on global attention mechanism
文献类型：会议论文
| 作者 | Wu T(吴彤)1,2,3; Ku T(库涛)2,3 ; Zhang H(张浩)2,3
|
| 出版日期 | 2019 |
| 会议日期 | August 28-30, 2019 |
| 会议地点 | Shenyang, China |
| 关键词 | Convolution Neural Networks Recurrent Neural Networks Image caption Global image feature extraction Global attention mechanism |
| 页码 | 1-6 |
| 英文摘要 | Convolution Neural Networks (CNN) and Recurrent Neural Networks (RNN), which are the main research methods of image caption, have developed rapidly. Nevertheless lacking of global consciousness in image caption has not been completely solved. Separation from the bottom-up visual attention mechanism and the top-down visual attention mechanism has been widely used in image description and visual question and answers. In this article, we put forward image description based on a global attention mechanism research methods. The global attention prior channel is added to the infrastructure to extract the global information features while learning the local features. The attention to the object and other outstanding level of image region is calculated, and the global image features are enhanced. |
| 源文献作者 | Chinese Society for Optical Engineering |
| 产权排序 | 1 |
| 会议录 | Second Target Recognition and Artificial Intelligence Summit Forum
 |
| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, USA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 978-1-5106-3631-6 |
| WOS记录号 | WOS:000546230500099 |
| 源URL | [http://ir.sia.cn/handle/173321/26419]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 通讯作者 | Wu T(吴彤) |
| 作者单位 | 1.Liaoning University, Shenyang 110036, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Wu T,Ku T,Zhang H. Research for image caption based on global attention mechanism[C]. 见:. Shenyang, China. August 28-30, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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