Rodent identification and analysis method based on deep learning and transfer learning

Abstract

The invention discloses a rodent identification and analysis method based on deep learning and transfer learning, and belongs to the technical field of animal classification and image processing. The method comprises the following steps: S1, carrying out rodent video acquisition and preprocessing; S2,making a rodent data set; S3, constructing and training a rodent model; S4,carrying out rodent detection; S5, carrying out rodent image cutting and super-resolution reconstruction; S6, segmenting each part of the rodent image; S7, carrying out data cleaning and calculation of all body index data; and S8, classifying rodents. The invention has the beneficial effects that detection, classification and segmentation of each part of the rodent are realized based on a deep learning method, and each body index data of the rodent is calculated, so that the rodent detection accuracy and efficiency are effectively improved, the traditional rodent classification mode is changed. And each part of the rodent can be automatically segmented, so that animal protection and pest prevention and control work can be favorably carried out.

Description

technical field [0001] The invention relates to the technical field of intelligent analysis, in particular to a method for identifying and analyzing rodents based on deep learning and transfer learning. Background technique [0002] Different types of rodents have different hazards, so the key points of prevention and control are different. Traditional monitoring methods are mainly physical instruments and chemical agents, which require professionals to operate, consume a lot of labor, and there are differences in human operations, which leads to subjective monitoring results. Influenced by factors, the monitoring effect is poor. With the continuous development of disciplines and technologies such as big data, Internet of Things, cloud computing, and artificial intelligence, a monitoring system has been constructed through the integration of multiple advanced technologies such as automatic image collection, digital image processing, artificial intelligence identification, an...

AI Technical Summary

Problems solved by technology

[0002] Different types of rodents have different hazards, so the key points of prevention and control are different. Traditional monitoring methods are mainly physical instruments and chemical agents, which require professionals to operate, consume a lot of labor, and there are differences in human operations, which leads to subjective monitoring results. Influenced by factors, the monitoring effect is poor

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