How Uber Uses Computer Vision
6 engineering articles about Computer Vision from Uber's engineering team
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The article discusses DeepETA, Uber's advanced model for predicting arrival times using deep learning techniques.
ApacheApache SparkComputer VisionDeep LearningMachine LearningSelf-AttentionTensorFlowTransformerTransformersXGBoost
Xinyu Hu, Olcay Cirit, Tanmay Binaykiya, Ramit Hora
15 min read
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The article discusses Meta-Graph, a framework for few-shot link prediction leveraging meta-learning techniques.
Ankit Jain, Piero Molino, Joey Bose, William Hamilton
13 min read
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In 2019, Uber AI advanced its mobility services through innovative applications of artificial intelligence across various domains, including computer vision, natural language processing, and deep l...
Zoubin Ghahramani
6 min read
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The article discusses Uber ATG's participation in three major conferences in 2019: ICCV, CoRL, and IROS.
Raquel Urtasun
6 min read
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The First Uber Science Symposium brought together experts from various fields to discuss advancements in reinforcement learning (RL), natural language processing (NLP), conversational AI, and deep ...
Computer VisionDeep LearningGenerative Adversarial NetworksMachine LearningPyTorchReinforcement LearningSwiftTensorFlow
Mahdi Namazifar, Gokhan Tur, Jeff Clune, John Sears, Rosanne Liu, Xu Ning, Zoubin Ghahramani
17 min read
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The article discusses SBNet, an open-source algorithm developed by Uber ATG that leverages activation block sparsity to enhance the speed of Convolutional Neural Networks (CNNs).
Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun
8 min read
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