Object Recognition Using Hierarchical Temporal Memory
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| Autores: | , |
|---|---|
| 格式: | capítulo de libro |
| Fecha de Publicación: | 2018 |
| 实物特征: | At this time, great effort is being directed toward developing problem-solving technology that mimics human cognitive processes. Research has been done to develop object recognition using Computer Vision for daily tasks such as secure access, traffic management, and robotic behavior. For this research, four different machine learning algorithms have been developed to overcome the computer vision problem of object recognition. Hierarchical temporal memory (HTM) is an emerging technology based on biological methods of the human cortex to learn patterns. This research applied an HTM algorithm to images (video sequences) in order to compare this technique against two others: support vector machines (SVM) and artificial neural networks (ANN). It was concluded that HTM was the most effective. |
| País: | Kérwá |
| 机构: | Universidad de Costa Rica |
| Repositorio: | Kérwá |
| OAI Identifier: | oai:kerwa.ucr.ac.cr:10669/74745 |
| 在线阅读: | https://link.springer.com/chapter/10.1007%2F978-3-319-76261-6_1 https://hdl.handle.net/10669/74745 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Computer vision hierarchical temporal memory |