首页> 外文会议>Australasian joint conference on artificial intelligence >A Neural Network Model of Visual Attention and Group Classification, and Its Performance in a Visual Search Task
【24h】

A Neural Network Model of Visual Attention and Group Classification, and Its Performance in a Visual Search Task

机译:视觉注意力和群体分类的神经网络模型及其在视觉搜索任务中的表现

获取原文

摘要

Humans can attend to and categorise objects individually, but also as groups. We present a computational model of how visual attention is allocated to single objects and groups of objects, and how single objects and groups are classified. We illustrate the model with a novel account of the role of stimulus similarity in visual search tasks, as identified by Duncan and Humphreys [1].
机译:人类可以单独地,也可以成组地对物体进行分类。我们提供了一个计算模型,该模型关于如何将视觉注意力分配给单个对象和对象组,以及如何将单个对象和组进行分类。正如邓肯和汉弗莱斯[1]所指出的,我们以新颖的方式说明了刺激相似性在视觉搜索任务中的作用,从而说明了该模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号