The invention discloses a tTarget detection method of a convolutional neural network based on pyramid input gain

Abstract

The invention relates to a target detection method of a convolutional neural network based on pyramid input gainconvolutional neural network target detection method based on pyramid input gain, and belongs to the technical field of computer vision and target detection. The target detection method is based on a convolutional neural network model PiaNet comprising a feature extraction module and a multi-task prediction module. The target detection method comprises a training stage and a test stage. A two-stage transfer learning strategy is adopted in the training stage, and the method comprisesthe steps of (1) data enhancement and data preprocessing, and a training set trained in the first stage, a training set trained in the second stage and a test set are generated; S; step (2), carryingout first-stage training in the binary classification network; (3) carrying out second-stage training to obtain a trained PiaNet network; I; in the test stage, a target is accurately detected, specifically, a test set is input into a trained PiaNet network, and the position of a detection box and a classification result are output through a multi-task loss function. And the method is wide in application range and has very high robustness.

Description

technical field [0001] The invention relates to a target detection method of a convolutional neural network based on pyramid input gain, and belongs to the technical field of computer vision and target detection. Background technique [0002] Target detection refers to finding the location information such as the specific position and size of all interested targets in the image. This problem is one of the basic problems in the fields of computer vision and pattern recognition. It is widely used in applications such as monitoring and analysis, face recognition, and nodule or tumor detection in medical CT images. [0003] Existing object detection methods are mainly divided into two categories: [0004] 1) Traditional object detection methods. Traditional target detection generally adopts the sliding window framework, which mainly includes steps such as image space segmentation, feature design and extraction, and classification recognition. It needs to search in several dime...

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to propose a method for target detection based on a convolutional neural network based on pyramidal input gain, aiming at the technical defects of low reliability and high rate of missed detection in the existing method for target

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