Site Name!

Object Detection and Recognition Using Deep Learning in OpenCV

18-06-2018, 10:29
Object Detection and Recognition Using Deep Learning in OpenCV

Object Detection and Recognition Using Deep Learning in OpenCV
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours 13M | 595 MB
Genre: eLearning | Language: English

This course teaches effective object recognition and its implementation with the powerful OpenCV libraries. You will learn how to enhance your OpenCV skills with deep learning. You will explore and master OpenCV for Object Recognition/Classification. The course explains all the necessary theory and concepts of computer vision, image processing, and machine learning. You also learn the practical application of OpenCV libraries. Its capabilities and functionality are shown along with a tutorial on how to set up a machine such that it's able to use OpenCV in codes. You will start by seeing how to work with images in OpenCV, enhancement and filtering in OpenCV. You will then move on to building an application which is capable of object recognition and performing homography. You will then move on to object classification and recognizing text in an image.

In the end, you will be able to use object recognition algorithm which will be used by you for practical application.




Object Detection and Recognition Using Deep Learning in OpenCV

Buy Premium Account To Get Resumable Support & Max Speed




Links are Interchangeable - No Password


/ Tags Cloud: Object, Detection, and, Recognition, Using
Dear visitor, you are browsing our website as Guest.
We strongly recommend you to register and login to view hidden contents.
art_links Category: ELearning

Important: WHEN ALL LINK OF ARTICLE DIE - PLEASE LEAVE COMMENT HERE. I WILL REUPLOAD IT.
You can Contact Us

Add comments

Your name:*
E-Mail:
Message:
  • winkwinkedsmileam
    belayfeelfellowlaughing
    lollovenorecourse
    requestsadtonguewassat
    cryingwhatbullyangry
Security Code: *
Click on the image to refresh the code if it cannot be viewed
Vote