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Insect feeding behavior analysis method and device and storage medium

A technology of behavior analysis and insects, applied in image analysis, neural learning methods, character and pattern recognition, etc., can solve problems such as low efficiency, low accuracy, and subjective assumptions, and achieve high efficiency, eliminate subjective assumptions, and high accuracy Effect

Inactive Publication Date: 2020-04-14
SOUTH CHINA NORMAL UNIVERSITY +1
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  • Application Information

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Problems solved by technology

However, the current analysis of insect feeding behavior is through manual close-up direct observation, manual recording and analysis, which is labor-intensive and has the possibility of subjective assumptions, low efficiency and low accuracy
At the same time, when the size of the insect is small, it is difficult to observe with the naked eye

Method used

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  • Insect feeding behavior analysis method and device and storage medium
  • Insect feeding behavior analysis method and device and storage medium
  • Insect feeding behavior analysis method and device and storage medium

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Embodiment Construction

[0043] The present invention will be further explained and described below in conjunction with the accompanying drawings and specific embodiments of the description. For the step numbers in the embodiment of the present invention, it is only set for the convenience of explanation and description, and there is no limitation on the order of the steps. The execution order of each step in the embodiment can be carried out according to the understanding of those skilled in the art Adaptive adjustment.

[0044] like figure 1 As shown, the insect feeding behavior analysis method of the present embodiment comprises the following steps:

[0045] Using the neural network to detect the insects in the video through the deep learning method, in which the video records the feeding status of multiple insects;

[0046] According to the detection results, the track of the insect is obtained;

[0047] According to the trajectory of the insect, the analysis result is obtained.

[0048] In th...

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Abstract

The invention discloses an insect feeding behavior analysis method and device and a storage medium. The method comprises the steps of employing a neural network to detect an insect in a video througha deep learning method, and recording the feeding states of a plurality of insects in the video; obtaining the track of the insect according to the detection result; and obtaining an analysis resultaccording to the track of the insect. According to the invention, detection and analysis can be carried out through the pre-recorded video, the neural network and the deep learning method; the track and the analysis result of the insect are obtained according to the detection result; manual observation, recording and analysis are not needed; the efficiency is high; subjective assumption is eliminated; and the accuracy is high. The insect feeding behavior analysis method and device and the storage medium can be widely applied to the technical field of insect behavior analysis.

Description

technical field [0001] The invention relates to the technical field of insect behavior analysis, in particular to a method, device and storage medium for analyzing insect feeding behavior. Background technique [0002] Insect ethology is a science that studies the behavior types, patterns and mechanisms of insects, and is an indispensable basic part of entomological research. Insect behavior can be used to analyze the intricate background and mechanism behind the behavior, and then the analysis results can be applied to prevent pests or kill insects. [0003] The behavior patterns of insects mainly include feeding behavior, reproductive behavior, orientation and movement behavior, communication behavior and so on. However, the current analysis of insect feeding behavior is through manual close-up direct observation, manual recording and analysis, which is labor-intensive and has the possibility of subjective assumptions, low efficiency and low accuracy. Meanwhile, when the...

Claims

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Application Information

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IPC IPC(8): G06T7/277G06K9/00
CPCG06T7/277G06T2207/10012G06T2207/30241G06T2207/20081G06T2207/20084G06V40/20G06T7/70G06T2207/10016G06T2207/20076G06T2207/20072G06N3/08G06T7/187G06T7/74G06T7/11G06T7/248G06N20/00G06T7/0016G06T2207/20021
Inventor 李娜李胜
Owner SOUTH CHINA NORMAL UNIVERSITY
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