Seed sorting based on deep learning is a promising method for seed breeding and subsequent processing products. In this paper, we proposed a rapid and efficient lightweight CNN model with a dual-branch network structure based on visual attention for seed sorting, denoted as SeedSortNet.
Aug 5, 2021
Apr 2, 2020 · The proposed sunflower seed sorting method based on heterogeneous convolutional network is robust to classify the seeds and the accuracy of data can reach 98.6 ...
Seed sorting has been extensively studied and is considered as image classification setting with the goal of distinguishing between normal and abnormal seeds.
Fast and High-Purity Seed Sorting Method Based on Lightweight CNN. https://doi.org/10.1007/978-981-15-3415-7_51. Journal: Communications in Computer and ...
A lightweight and fast CNN model is constructed by using heterogeneous convolution layer instead of standard convolutional layer. Specially, we compare the ...
Zhengguang Luan, Chunlei Li, Shumin Ding, Qiang Guo, Bicao Li: Fast and High-Purity Seed Sorting Method Based on Lightweight CNN. BIC-TA (2) 2019: 607-615.
In this study, a rapid and highly efficient lightweight CNN based on visual attention, namely SeedSortNet, is proposed for seed sorting. First, a dual ...
Experimental results show that SeedSortNet achieves the accuracy rates of 97.33% and 99.56% on the maize seed dataset and sunflower seed dataset, respectively, ...
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Aug 5, 2021 · In this study, a rapid and highly efficient lightweight CNN based on visual attention, namely SeedSortNet, is proposed for seed sorting. ... In ...
Missing: Method | Show results with:Method
Nov 9, 2021 · A method of combining layer pruning and filter pruning is proposed to realize fast and high-purity seed grading.