Diatom detection and recognition method based on deep learning algorithm

Abstract

The embodiment of the invention discloses a diatom detection and recognition method based on a deep learning algorithm. The diatom detection and recognition method is used for solving the problems oflow recognition efficiency and inaccurate recognition caused by too many types and complex backgrounds in the diatom inspection process. The embodiment of the invention comprises the following steps:S1, obtaining various diatom types of images, and making a data set according to a Pascal VOC2007 data set format; S2, training a target detection model for various diatom targets through a deep learning target detection algorithm; S3, using the trained Faster R-CNN network model to detect diatom targets in an image to be detected, and the image entering the convolutional layer of the Fast R-CNN network model, inputting the feature map output by the last shared convolutional layer into an RPN network model to generate candidate regions where targets may exist, outputting the central coordinates and the width and the height of the regions, and inputting the features of the candidate regions into subsequent classification and frame regression part in the Fast R-CNN, to obtain a target type and refined position information.

Description

technical field [0001] The invention relates to the technical field of biological detection and identification, in particular to a diatom detection and identification method based on a deep learning algorithm. Background technique [0002] Diatoms are a kind of aquatic single-celled plants that are widely distributed on the earth. Because they are very sensitive to changes in water temperature and nutrient concentration, they are often used as reference indicators for water quality. On the other hand, most of the corpses drowned in water are found to be in a state of high corruption. Diatom testing is the most effective method for diagnosing drowning in corpses, and it plays a very important role in forensic examination. [0003] At present, there are two main methods for classifying and identifying diatom images obtained by sampling in forensic medical examination. One is to rely on manual identification, and the other is to use machine learning methods. Among them, the dia...

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Problems solved by technology

[0005] The embodiment of the present invention discloses a diatom detection and identification method based on a deep learning algorithm, which is used to solve the problems of low recognition efficiency and inaccurate recognition caused by too many types of diatoms and complex backgrounds in the diatom inspection process

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