Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Christian Bilgera"'
Publikováno v:
Sensors, Vol 18, Iss 12, p 4484 (2018)
Convolutional Long Short-Term Memory Neural Networks (CNN-LSTM) are a variant of recurrent neural networks (RNN) that can extract spatial features in addition to classifying or making predictions from sequential data. In this paper, we analyzed the u
Externí odkaz:
https://doaj.org/article/c50c69e101ff4023b5af8ee5b4903127
Autor:
Chee-Siang Leow, Haruka Matsukura, Hiromitsu Nishizaki, Christian Bilgera, Akifumi Yamamoto, Naoki Sawada, Hiroshi Ishida, Maki Sawano
Publikováno v:
2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN).
In outdoor environments, fluctuating airflow and gas distribution make gas source localization (GSL) tasks difficult. In our research, we use neural networks (NNs) to overcome these difficulties by applying long short-term memory deep neural networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9862997f61d916c95c234a2e67f27b8a
https://doi.org/10.1109/isoen.2019.8823160
https://doi.org/10.1109/isoen.2019.8823160
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 18
Issue 12
Sensors, Vol 18, Iss 12, p 4484 (2018)
Sensors
Volume 18
Issue 12
Sensors, Vol 18, Iss 12, p 4484 (2018)
Convolutional Long Short-Term Memory Neural Networks (CNN-LSTM) are a variant of recurrent neural networks (RNN) that can extract spatial features in addition to classifying or making predictions from sequential data. In this paper, we analyzed the u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39a0a6b809faab7141268da1f02ba473
http://europepmc.org/articles/PMC6308690
http://europepmc.org/articles/PMC6308690
Autor:
Tsuyoshi Shimmura, Akifumi Yamamoto, Minami Owada, Christian Bilgera, Hiroshi Ishida, Tomoki Uno
Publikováno v:
The Proceedings of Mechanical Engineering Congress, Japan. 2019:S11508P
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c474a6de18b810f0f3f93748f9b16d70
https://doi.org/10.1299/jsmemecj.2019.s11508p
https://doi.org/10.1299/jsmemecj.2019.s11508p