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180 results for "uber fleet" across all locations

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Products 5 de febrero de 2018 / Chennai

Your PREMIER ride is arriving now

Welcome to PREMIER, your very own personal space!

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Products 17 de marzo de 2015 / Dubai

Smart City Technology: How Uber works in the UAE

Recently we have been asked a number of questions about how Uber works in different parts of the world and in the UAE. Simply put, our team at Uber believes in choice, and we believe our technology can complement cities, such as Dubai, boost their current transportation network in order to reduce congestion, increase safety and service levels, and optimize the efficiency of public transport systems.

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Products 19 de noviembre de 2018 / Abu Dhabi

Abu Dhabi, we’re back!

After 2 years off the road, Uber services are now available again in Abu Dhabi starting November 19.

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Products 11 de septiembre de 2017 / Ahmedabad

PREMIER flags off with Rider Zero, Kangana Ranaut

Welcome to PREMIER, your very own personal space.

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Products 3 de septiembre de 2018 / Dubai

What do you need to become an Uber driver-partner in Dubai?

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Drive 28 de marzo de 2018 / Basel

Starting A Limousine Service With The Right Knowledge

Ermin hat seinen Traum vom eigenen Chauffeur-Service verwirklicht. Wir haben Ihn gefragt, worauf es ankommt, wenn man ein solches Unternehmen aufbaut.

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Business 18 de junio de 2018 / Global

New trip allowances to help manage your account

Introducing new features to manage the number of trips your employees can take in a given day or month, and per-day and per-trip allowances.

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Products 9 de julio de 2012 / Washington, DC

Strike Down the Minimum Fare Language in the DC Uber Amendment

Please stand with us and encourage the DC City Council to strike down the MINIMUM FARE language from the Uber Amendment in tomorrow’s Taxi Improvement Bill.

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Promotions 10 de marzo de 2014 / Washington, DC

Join One of Uber’s Fastest Growing Cities, DC!

Uber AI, Engineering 16 de septiembre de 2019 / Global

Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving

N. Djuric, V. Radosavljevic, H. Cui, T. Nguyen, F.-C. Chou, T.-H. Lin, N. Singh, J. Schneider
We introduce an approach that takes into account a current world state and produces rasterized representations of each traffic actor’s vicinity. The raster images are then used as inputs to deep convnets to infer future movement of actors while also accounting for and capturing inherent uncertainty of the prediction task, with extensive experiments on real-world data strongly suggest benefits of the proposed approach. [PDF]
Winter Conference on Applications of Computer Vision (WACV), 2020