Patent ID: 11790040

Abstract:
The present disclosure provides a method for object detection and recognition based on a neural network. The method includes: adding a detection layer following three detection layers of an existing YOLOv5 network model, to construct a new YOLOv5 network model; then, training the new YOLOv5 network model by considering an overlapping area between a predicted box and a ground truth box, a center-to-center distance between the two boxes, and an aspect ratio of the two boxes; and finally, inputting a to-be-detected image into the trained new YOLOv5 network model, outputting a predicted box of an object and probability values corresponding to a class to which the object belongs, and setting a class corresponding to a maximum probability value as a predicted class of the object in the to-be-detected image. This method can quickly and effectively detect multiple classes of objects. Especially, a detection effect for small objects is more ideal.