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Débute 4 June 2026 12:34

Se termine 4 June 2026

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Computer Vision for Engineering and Science

Explorez la pointe de la technologie avec notre spécialisation en Vision par Ordinateur pour l'Ingénierie et la Science. Les caméras jouent un rôle essentiel dans une panoplie de technologies innovantes, allant de l'aide aux systèmes autonomes dans la navigation environnementale à l'assistance aux chirurgiens pour des procédures minimalement invasi.
via Coursera  Specialization

106 Cours


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Aperçu

Explore the forefront of technology with our Computer Vision for Engineering and Science specialization. Cameras play a pivotal role in an array of innovative technologies, from aiding autonomous systems in environment navigation to assisting surgeons with minimally invasive procedures.

Mastering computer vision techniques is crucial for engineers aiming to extract vital information from images and videos. This comprehensive course, offered on Coursera, will equip you with the essential skills for numerous high-demand jobs today.

You will learn to:

  • Perform sophisticated object detection
  • Train robust image classification models
  • Employ features for object tracking and image alignment
  • Identify motion within video content
  • Implement advanced multi-object tracking techniques

Throughout this specialization, MATLAB, a preferred tool among millions in engineering and science, will be used. Participants will enjoy free access to MATLAB, ensuring they have the requisite tools to complete their computer vision projects.

While some previous experience in image processing is beneficial, beginners are encouraged to start with the Image Processing for Engineering and Science specialization to build a foundational understanding. Dive into the world of machine learning, computer vision, and more with this Coursera and MATLAB collaboration, paving your path in Machine Learning, Computer Vision, MATLAB, Image Classification, and Object Detection domains.


Enseigné par

Amanda Wang, Brandon Armstrong, Isaac Bruss, Matt Rich and Megan Thompson


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