Research on the Classification of Sun-Dried Wild Ginseng Based on an Improved ResNeXt50 Model
Source abstract
Abstract
Ginseng is a common medicinal herb with high value due to its unique medicinal properties. Traditional methods for classifying ginseng rely heavily on manual judgment, which is time-consuming and subjective. In contrast, deep learning methods can objectively learn the features of ginseng, saving both labor and time. This experiment proposes a ginseng-grade classification model based on an improved ResNeXt50 model. First, each convolutional layer in the Bottleneck structure is replaced with the corresponding Ghost module, reducing the model’s computational complexity and parameter count without compromising performance. Second, the SE attention mechanism is added to the model, allowing it to capture feature information more accurately and precisely. Next, the ELU activation function replaces the original ReLU activation function. Then, the dataset is augmented and divided into four categories for model training. A model suitable for ginseng grade classification was obtained through experimentation. Compared with classic convolutional neural network models ResNet50, AlexNet, iResNet, and EfficientNet_v2_s, the accuracy improved by 10.22%, 5.92%, 4.63%, and 3.4%, respectively. The proposed model achieved the best results, with a validation accuracy of up to 93.14% and a loss value as low as 0.105. Experiments have shown that this method is effective in recognition and can be used for ginseng grade classification research.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Traditional Chinese Medicine Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Information Technology, Jilin Agricultural University, Changchun 130118, China
College of Internet of Things Engineering, Wuxi University, Wuxi 214105, China
Information Center of Jilin Agricultural University, Changchun 130118, China
Funding
National Natural Science Foundation of China · Jilin Province Science and Technology Development Plan Key Research and Development Project · Wuxi University Research Start-up Fund for Introduced Talents · Jiangsu Engineering Research Center of Hyperconvergence application and security of IoT devices · Jiangsu Foreign Expert Workshop · Jiangsu Foreign Expert Workshop; Wuxi City Internet of Vehicles Key Laboratory
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