HVGH: Unsupervised Segmentation for High-Dimensional Time Series Using Deep Neural Compression and Statistical Generative Model

Humans perceive continuous high-dimensional information by dividing it into meaningful segments, such as words and units of motion. We believe that such unsupervised segmentation is also important for robots to learn topics such as language and motion. To this end, we previously proposed a hierarchi...

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Detalles Bibliográficos
Publicado en:Front Robot AI
Autores principales: Nagano, Masatoshi, Nakamura, Tomoaki, Nagai, Takayuki, Mochihashi, Daichi, Kobayashi, Ichiro, Takano, Wataru
Formato: Artigo
Lenguaje:Inglês
Publicado: Frontiers Media S.A. 2019
Materias:
Robotics and AI
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC7805757/
https://ncbi.nlm.nih.gov/pubmed/33501130
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frobt.2019.00115
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