Crop seedling and weed detection method and system based on deep learning

Abstract

The invention discloses a crop seedling and weed detection method and system based on deep learning, and the method comprises the steps: obtaining a crop seedling and associated weed image data set, and dividing the image data set into a training set, a verification set and a test set; labeling the training set image, the verification set image and the test set image, and amplifying the training set image; constructing an SSD detection model on a kernel deep learning framework, designing a lightweight dense connection network as a pre-feature extraction network, and fusing feature informationof different levels in the pre-feature extraction network and an extension network; inputting a training set into the improved SSD detection model for training to obtain a crop weed recognition and positioning model; inputting the test set into the trained model, and outputting types and position information of crops and weeds; according to the method, t. The problems of low detection precision, long consumed time and the like of a traditional crop and weed identification method are solved, and the accuracy and real-time performance of crop and weed detection are improved.

Description

technical field [0001] The invention relates to the field of detection of agricultural crops and weeds, in particular to a method and system for detecting crop seedlings and weeds based on deep learning. Background technique [0002] During the growth of crops, weeds compete with crops for water, nutrients and light, hindering the normal growth of crops and adversely affecting agricultural production. Weed control is an important link in agricultural production and plays an important role in improving crop yield and quality. [0003] With the development of precision agriculture technology, automated mechanical weeding that does not rely on herbicides has gradually become a research hotspot in the field of weed control at home and abroad. In the process of automatic mechanical weeding operation, how to detect and identify crops and weeds in real time and accurately is the key premise to achieve precise and efficient weeding. [0004] The traditional crop and weed detection...

AI Technical Summary

Problems solved by technology

At present, the research on crop and weed recognition based on deep learning generally uses multi-layer deep convolutional neural network for feature extraction. By increasing the depth and width of the network to achi

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