Object detection had an explosion concerning both applications and research in recent years. Object detection is a problem of importance in computer vision. Similar to image classification tasks, deeper networks have shown better performance in detection. At present, the accuracy of these techniques is excellent. Hence it used in many applications.
Image classification labels the image as a whole. Finding the position of the object in addition to labeling the object is called object localization. Typically, the position of the object is defined by rectangular coordinates. Finding multiple objects in the image with rectangular coordinates is called detection. Here is an example of object detection:
The image shows four objects with bounding boxes. We will learn algorithms that can perform the task of finding the boxes. The applications are enormous in robot vision, such as self-driving cars and industrial objects. We can summarize localization and detection tasks...
