Object Detection using Deep Learning | Getting started with OpenCV series

In this video, we will see how to perform Deep Learning based Object Detection. We will use SSD Neural Network trained using Tensorflow.
With the rise of autonomous vehicles, smart video surveillance, facial detection, and various people-counting applications, fast and accurate object detection systems are rising in demand. These systems involve not only recognizing and classifying every object in an image but localizing each one by drawing the appropriate bounding box around it. This makes object detection significantly harder than its traditional computer vision predecessor, image classification.
Object recognition refers to a collection of related tasks for identifying objects in digital photographs.
Region-Based Convolutional Neural Networks, or R-CNNs, is a family of techniques for addressing object localization and recognition tasks designed for model performance.
You Only Look Once, or YOLO is a second family of techniques for object recognition designed for speed and real-time use.

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We can train our own deep learning object detection models in OpenCV
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