Presentation: Dive Deep into Building Computer Vision Systems for Self-flying Drones
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Abstract
Every industrial drone in the world needs to see the world the way a pilot does, an obvious, but non-trivial feat of engineering. In this talk the challenge of building a computer vision/AI "sense and avoid" system is discussed, along with the challenges of a constrained cost/size/weight/power design environment. It’ll dive into deep learning training, simulation, and real-world aircraft testing with near-mid-air collisions, in order to keep these drones safe while they get integrated into the national airspace!
2019 Tracks
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Groking Timeseries & Sequential Data
Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.
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Deep Learning in Practice
Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.
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AI Meets the Physical World
Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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Solving Software Engineering Problems with Machine Learning
Interesting machine learning use cases changing how we develop software today, including planned topics touching on infrastructure optimization, developer experience, security, and more.
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Predictive Architectures in the Real World
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.