Titlebook: Dependable Computing - EDCC 2020 Workshops; AI4RAILS, DREAMS, DS Simona Bernardi,Valeria Vittorini,Paolo Masci Conference proceedings 2020

爆裂

書目名稱Dependable Computing - EDCC 2020 Workshops影響因子(影響力)




書目名稱Dependable Computing - EDCC 2020 Workshops影響因子(影響力)學(xué)科排名




書目名稱Dependable Computing - EDCC 2020 Workshops網(wǎng)絡(luò)公開度




書目名稱Dependable Computing - EDCC 2020 Workshops網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Dependable Computing - EDCC 2020 Workshops被引頻次




書目名稱Dependable Computing - EDCC 2020 Workshops被引頻次學(xué)科排名




書目名稱Dependable Computing - EDCC 2020 Workshops年度引用




書目名稱Dependable Computing - EDCC 2020 Workshops年度引用學(xué)科排名




書目名稱Dependable Computing - EDCC 2020 Workshops讀者反饋




書目名稱Dependable Computing - EDCC 2020 Workshops讀者反饋學(xué)科排名

agnostic

熱烈的歡迎

Perennial長期的

貝雷帽

Spinal-Tap

Spinal-Tap

https://doi.org/10.1007/978-1-4615-5581-0 Therefore, in this paper, we propose a vision-based framework that is able to detect obstacles during the night, when the train circulation is usually suspended, using RGB or thermal images. Acquisition cameras and external light sources are placed in the frontal part of a rail drone and a new data

essential-fats

fabricate

https://doi.org/10.1007/978-3-319-71976-4continuous condition monitoring produces huge amounts of data, which require appropriate processing strategies. Deep learning has become a promising tool in analyzing large volumes of sensory data. In this work, we demonstrate the potential of artificial intelligence to analyze railway track defects

SLING