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    Hands-On Vision and Behavior for Self-Driving Cars. Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4 Luca Venturi, Krishtof Korda

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Hands-On Vision and Behavior for Self-Driving Cars. Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4 Luca Venturi, Krishtof Korda - okladka książki

    Hands-On Vision and Behavior for Self-Driving Cars. Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4 Luca Venturi, Krishtof Korda - okladka książki

    Hands-On Vision and Behavior for Self-Driving Cars. Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4 Luca Venturi, Krishtof Korda - audiobook MP3

    Hands-On Vision and Behavior for Self-Driving Cars. Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4 Luca Venturi, Krishtof Korda - audiobook CD

    Autorzy:
    Luca Venturi, Krishtof Korda
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    374
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Zostało Ci na świąteczne zamówienie opcje wysyłki »
    The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field.
    You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller.
    By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers.

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    O autorach książki

    Luca Venturi has extensive experience as a programmer with world-class companies, including Ferrari and Opera Software. He has also worked for some start-ups, including Activetainment (maker of the world's first smart bike), Futurehome (a provider of smart home solutions), and CompanyBook (whose offerings apply artificial intelligence to sales). He worked on the Data Platform team at Tapad (Telenor Group), making petabytes of data accessible to the rest of the company, and is now the lead engineer of Piano Software's analytical database.
    Krishtof Korda grew up in a mountainside home over which the US Navy's Blue Angels flew during the Reno Air Races each year. A graduate from the University of Southern California and the USMC Officer Candidate School, he set the Marine Corps obstacle course record of 51 seconds. He took his love of aviation to the USAF, flying aboard the C-5M Super Galaxy as a flight test engineer for 5 years, and engineered installations of airborne experiments for the USAF Test Pilot School for 4 years. Later, he transitioned to designing sensor integrations for autonomous cars at Lyft Level 5. Now he works as an applications engineer for Ouster, integrating LIDAR sensors in the fields of robotics, AVs, drones, and mining, and loves racing Enduro mountain bikes.

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