Computer Vision kurser och utbildning
Computer Vision är ett fält som innebär att automatiskt extrahera, analysera och förstå användbar information från digitala medier. NobleProg onsite live Computer Vision kurser visar genom interaktiva diskussioner och handson öva grunderna i Computer Vision som deltagare steg genom skapandet av enkla Computer Vision-appar. Datorsynsutbildning finns i olika format, inklusive live-träning och live-instruktörsutbildning med hjälp av en interaktiv fjärrskrivbordsinstallation. Lokal datorvisionsutbildning kan utföras live på kundlokaler eller i NobleProgs lokala utbildningscenter ..
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| Kod | Namn | Varaktighet | Översikt |
|---|---|---|---|
| simplecv | Computer Vision with SimpleCV | 14 hours | SimpleCV is an open source framework — meaning that it is a collection of libraries and software that you can use to develop vision applications. It lets you work with the images or video streams that come from webcams, Kinects, FireWire and IP cameras, or mobile phones. It’s helps you build software to make your various technologies not only see the world, but understand it too. Audience This course is directed at engineers and developers seeking to develop computer vision applications with SimpleCV. |
| opencv | Computer Vision with OpenCV | 28 hours | OpenCV (Open Source Computer Vision Library: http://opencv.org) is an open-source BSD-licensed library that includes several hundreds of computer vision algorithms. Audience This course is directed at engineers and architects seeking to utilize OpenCV for computer vision projects |
| patternmatching | Pattern Matching | 14 hours | Pattern Matching is a technique used to locate specified patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not. Audience Engineers and developers seeking to develop machine vision applications Manufacturing engineers, technicians and managers Format of the course This course introduces the approaches, technologies and algorithms used in the field of pattern matching as it applies to Machine Vision. |
| marvin | Marvin Image Processing Framework - Creating Image and Video Processing Applications with Marvin | 14 hours | Marvin is an extensible, cross-platform, open-source image and video processing framework developed in Java. Developers can use Marvin to manipulate images, extract features from images for classification tasks, generate figures algorithmically, process video file datasets, and set up unit test automation. Some of Marvin's video applications include filtering, augmented reality, object tracking and motion detection. In this course participants will learn the principles of image and video analysis and utilize the Marvin Framework and its image processing algorithms to construct their own application. Audience Software developers wishing to utilize a rich, plug-in based open-source framework to create image and video processing applications Format of the course The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks which allow them to practice the concepts learned. By the end of the class, participants will have developed their own application using the Marvin Framework and libraries. |
| pythoncomputervision | Computer Vision with Python | 14 hours | Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of set of simple Computer Vision application using Python. By the end of this training, participants will be able to: Understand the basics of Computer Vision Use Python to implement Computer Vision tasks Build their own face, object, and motion detection systems Audience Python programmers interested in Computer Vision Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
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