Salient regions detection using convolutional neural networks and color volume

摘要：

　　Convolutional neural network is an important technique in machine learning,pattern recognition and image processing.In order to reduce the computational burden and extend the classical LeNet-5 model to the field of saliency detection,we propose a simple and novel computing model based on LeNet-5 network.In the proposed model,hue,saturation and intensity are utilized to extract depth cues,and then we integrate depth cues and color volume to saliency detection following the basic structure of the feature integration theory.Experimental results show that the proposed computing model outperforms some existing state-of-the-art methods on MSRA1000 and ECSSD datasets.

作者: Guang-Hai Liu Yingkun Hou

作者单位: College of Computer Science and Information Technology,Guangxi Normal University,Guilin,China School of Information Science and Technology,Taishan University,Taian,Shandong 271000,China

会议类型: 国际会议

会议名称: The 1st International Symposium on Application of Materials Science and Energy Materials (SAMSE 2017)

会议地点: 上海

会议语种:英文

页码: 1-6

在线出版日期: 2017-12-28（万方平台首次上网日期，不代表论文的发表时间）