
EFE Code 3 model of RT1 excellent model - WorthPoint
This Code 3 EFE model of London Transport's first RT - RT1 is not a simple re-do of EFE's early type RT but a conversion from a normal RT. It has the correct shape drivers cab and both front and rear roof boxes.
Modern buses - EFE SHOWBUS International 2009 photos
Click RT1 to return to the 2009 index Beestons of Hadleigh in Suffolk has invested in two new doubledeckers. Both are coaches, though this 100 seater Volvo B9TL with Optare Olympus body is normally geared towards school contracts, but the vehicle is a good back up to the two Van Hool Astrobel coaches in the fleet.
Efe Rt Buses for sale - eBay
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Bristols & Leyland National - EFE SHOWBUS International 2009 …
Looking like new in the SHOWBUS sunshine is former Eastern National 1516 (FWC439H), a Bristol RELL6G with the third style of ECW body fitted to the chassis, with a deep flat windscreen. Sister vehicle, 1510, is about to be released in NBC livery as model 25004 by EFE.
Modern coaches - EFE SHOWBUS International 2009 photos
Click RT1 to return to the 2009 index What about the workers? Chambers of Stevenage brought along this pair of disabled accessible Marcopolo bodied coaches which operated on the site shuttle for part of the day.
Modern Singledeckers - EFE SHOWBUS International 2009 photos
Click RT1 to return to the 2009 index Returning to SHOWBUS is E930PBE, the Leyland Tiger/Alexander P new to Grimsby-Cleethorpes. This year it brought an all orange Mercedes, M883DDS as a late entrant.
EFE RT1 BUS LONDON TRANSPORT ROUTE 177 1/76 CODE 3
1/76 Scale diecast model by EFE. Code 3 model. AEC RT Bus in London Transport livery. RT1 is on route 177 to Abbey Wood Garage with adverts for Maples Carpets and Brymay. Ref no: Code 3 conversion...from 39294949
RT-1: ROBOTICS TRANSFORMER FOR REAL WORLD CONTROL AT …
RT-1 能够学习执行大量指令,并且在zero-shot 设置中对新指令(任务和物体分别见过,但是组合在一起没见过)、其余物体的干扰和新环境(桌布、光照等)具有泛化能力。
Efe (@efeme_rt1) • Instagram photos and videos
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Robot Transformer 1(RT-1) - 知乎 - 知乎专栏
RT1使用了一种基于 FiLM 的方法,可以根据语言指令动态地调节图像特征,从而实现语言条件学习的效果。 RT-1的输入是一段短的图像序列和一个指令,输出是每个时间步的一个动作。 为了实现这一点,RT-1的架构包括几个部分: (1)将图像和指令通过一个ImageNet预训练的卷积网络(EfficientNet-B3)进行编码,该网络通过FiLM层(Perez et al., 2018)根据一个预训练的指令嵌入进行条件化,提取视觉-语言特征。 (2)利用这些特征通过一个 TokenLearner (Ryoo et …
- 某些结果已被删除