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一种基于语义的资源受限设备机器感知的有效位向量方法An Efficient Bit Vector Approach to Semantics-based Machine Perception in Resource-Constrained Devices |
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| 课程网址: | http://videolectures.net/iswc2012_henson_constrained_devices/ |
| 主讲教师: | Cory Henson |
| 开课单位: | 莱特州立大学 |
| 开课时间: | 2012-12-03 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The primary challenge of machine perception is to define efficient computational methods to derive high-level knowledge from low-level sensor observation data. Emerging solutions are using ontologies for expressive representation of concepts in the domain of sensing and perception, which enable advanced integration and interpretation of heterogeneous sensor data. The computational complexity of OWL, however, seriously limits its applicability and use within resource-constrained environments, such as mobile devices. To overcome this issue, we employ OWL to formally define the inference tasks needed for machine perception – explanation and discrimination – and then provide efficient algorithms for these tasks, using bit-vector encodings and operations. The applicability of our approach to machine perception is evaluated on a smart-phone mobile device, demonstrating dramatic improvements in both efficiency and scale. |
| 关 键 词: | 机器感知; 低水平传感器; 观测数据 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-05-08：cwx |
| 阅读次数: | 82 |