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Put AI to work
April 10-11, 2018: Training
April 11-13, 2018: Tutorials & Conference
Beijing, CN

Schedule: 计算机视觉(Computer Vision) sessions

The renewed interest in AI can be traced to the success of deep learning architectures in image classification and speech recognition. Since its emergence in 2012, computer vision researchers continue to push deep learning architectures, most recently towards content generation via semi-supervised learning. Computer vision is an active research area where ideas are being turned into real-world products.

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09:3009:45 Thursday, April 12, 2018
Reza Zadeh (Matroid | Stanford)
Reza Zadeh details three challenges on the way to building cutting-edge ML products, with a focus on computer vision, offering examples, recommendations, and lessons learned. Read more.
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10:0010:15 Thursday, April 12, 2018
Location: 紫金大厅A(Grand Hall A)
Hui Xiong (Baidu)
本议题中我将介绍数据驱动人工智能带来的一些新兴机会和挑战,同时关注深度学习、推荐引擎和数据密集型计算平台的趋势,以及自动驾驶、对话式AI、位置感知社交媒体和视觉搜索。 Read more.
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11:1511:55 Thursday, April 12, 2018
Reza Zadeh (Matroid | Stanford)
Reza Zadeh offers an overview of Matroid’s Kubernetes deployment, which provides customized computer vision and stream monitoring to a large number of users, and demonstrates how to customize computer vision neural network models in the browser. Along the way, Reza explains how Matroid builds, trains, and visualizes TensorFlow models, which are provided at scale to monitor video streams. Read more.
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09:2509:40 Friday, April 13, 2018
Location: 紫金大厅A(Grand Hall A)
Sherry Moore (Google)
人工智能已经不是未来的科技,它正快速地成为我们日常生活的一部分。在本演讲中,谷歌TensorFlow的领导者Sherry Moore将会介绍机器学习是如何造福世界的,特别是对于科学的发展。她将会讨论她自己的关于学习如何学习(AutoML)的工作以及几个在中国和全世界使用TensorFlow和机器学习的迷人案例。
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10:1510:35 Friday, April 13, 2018
Location: 紫金大厅A(Grand Hall A)
Hsiao-Wuen Hon (微软亚洲研究院 (Microsoft Research Asia))
人工智能已经引发了众多关注和讨论,而关于人类智能和人工智能孰优孰劣的辩论也不断升温。在这个主题演讲中,洪小文博士将介绍人工智能(AI)以及人类智能(HI)的历史。从历史的维度,以深刻的洞察,阐述AI和HI是如何彼此交织并共同进化的,并预示AI和HI可能的未来。 Read more.
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11:1511:55 Friday, April 13, 2018
模型与方法 (Models and Methods)
Location: 多功能厅3A+B (Function Room 3A+B)
Baining Guo (微软亚洲研究院 (Microsoft Research Asia))
关于微软亚洲研究院通过人工智能技术进行图像合成的最新研究概述。从把普通照片变成毕加索风格的绘画,到生成莱昂纳多·迪卡普里奥(Leonardo DiCaprio)的新图像,我们展示了深度学习所带来的新的可能性。 Read more.
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13:1013:50 Friday, April 13, 2018
实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B)
邱鑫 (Intel)
BigDL(基于Apache Spark的大数据分布式的深度学习框架)为大规模图像处理提供了丰富的端到端支持。我们将介绍如何使用BigDL搭建灵活性和高可扩展性的端到端深度学习应用程序。我们还将分享我们在京东构建大规模图像特征提取流水线的经验。 Read more.
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14:5015:30 Friday, April 13, 2018
实施人工智能 (Implementing AI)
Location: 多功能厅3A+B (Function Room 3A+B) Level:
李忠伟 (深圳普思英察科技有限公司)
本演讲主要阐述视觉智能(Visual Intelligence)的定义,传感器分类和介绍,流行算法和介绍,应用场景以及创新点。 介绍视觉传感器的发展历史以及分类,包括被动光摄像头和主动光摄像头以及其他衍生传感器 介绍基于视觉的算法:深度学习算法和SLAM算法 介绍视觉智能在机器人行业中的应用,包括家庭机器人,服务类机器人,无人驾驶汽车。 最后介绍多传感器融合的解决方案在机器人行业的应用以及必要性。 Read more.