Deep Neural Networks for Object Detection Deep Neural Networks for Object Detection
Paper summary **Object detection** is the task of drawing one bounding box around each instance of the type of object one wants to detect. Typically, image classification is done before object detection. With neural networks, the usual procedure for object detection is to train a classification network, replace the last layer with a regression layer which essentially predicts pixel-wise if the object is there or not. An bounding box inference algorithm is added at last to make a consistent prediction.

Loading...
Your comment:


Short Science allows researchers to publish paper summaries that are voted on and ranked!
About