Real-Time Temporal Differentiation of Coherent Images

相干图像的实时时间微分

• 批准号: 8714699
• 负责人: Mark Cronin-Golomb
• 金额: $ 3万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-06-01 至 1988-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8714699&HistoricalAwards=false
• 关键词: Real; Time; Temporal; Differentiation; Coherent

The area of novelty filtering (detecting changes in a pattern) is of importance to investigators working with optical and electronic neural systems for at least two reasons. Firstly, for transmission of information, much less capacity is required when only changes in spatial or temporal pattern are used (unless the pattern or scene changes totally and abruptly). Secondly, in pattern recognition, detecting changes or motion is of obvious importance. The purpose of the research is the development of optical neural systems which have the potential of sensing changes in a three-dimensional scene.

对于使用光学和电子神经系统工作的研究者至少有两个原因，新颖性过滤区域（检测模式的变化）对于研究人员至关重要。 首先，对于信息传输，仅使用空间或时间模式的变化（除非模式或场景都完全和突然变化）时所需的容量要少得多。 其次，在模式识别中，检测变化或运动至关重要。 该研究的目的是开发光学神经系统，这些神经系统具有在三维场景中传感变化的潜力。