.png){kind=icon}
返回
Emergent spatio-temporal multimodal learning using a developmental network
.png){kind=icon}
PRE
AI
DOI：10.1007/s10489-018-1337-5.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Conventional machine learning needs humans to train each module with hand-handcrafted data and symbols manually, and the results of these methods are confined to particular tasks. To address this limitation, in this paper we design a multimodal autonomous learning architecture based on a developmental network for the audio and vision co-development. The developmental network is a biological inspired mechanism, which can make an agent to develop and integrate audition and vision simultaneously. Furthermore, synapse maintenance is introduced in the vision information learning to enhance the video recognition rate and neuron regenesis mechanism is implemented to enhance the network usage efficiency. In the experiments, a number of fundamental words are acquired and identified using the proposed learning methodology without any prior knowledge about the objects or the verbal questions before running. The experiments show that the proposed learning method can achieve significantly high recognition rates in comparison with the state-of-the-art method.
Keyword:
Multimodal learning
Developmental network
Synapse maintenance
Skull-closed
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.6K
被引数:
1.7W
机构
引用论文
Supercritical fluid processing of nitric acid treated nitrogen doped graphene with enhanced electrochemical supercapacitance.png)
RSC Adv.
RSC Adv.IF0
PREAI
分享收藏分享收藏A deep architecture for audio-visual voice activity detection in the presence of transientsSIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏
查看更多内容