An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices
Deer antler slices are highly valued in Chinese herbal medicine due to their medicinal properties. However, the current process for classifying these slices is time-consuming and subjective. To overcome this issue, we propose an intelligent classification and recognition model based on the Res2Net a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10164254/ |
| _version_ | 1797680917389508608 |
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| author | Dongming Li Rui Yao Chenglin Yang Chunxi Zhao Lijuan Zhang |
| author_facet | Dongming Li Rui Yao Chenglin Yang Chunxi Zhao Lijuan Zhang |
| author_sort | Dongming Li |
| collection | DOAJ |
| description | Deer antler slices are highly valued in Chinese herbal medicine due to their medicinal properties. However, the current process for classifying these slices is time-consuming and subjective. To overcome this issue, we propose an intelligent classification and recognition model based on the Res2Net architecture. Our neural network utilizes an inverse bottleneck structure to enhance grouped convolution and reduce model parameters and computation time. Additionally, we integrate an improved grouped convolution into the Res2Net model and leverage the efficient channel attention (ECA) mechanism to improve feature extraction. Our model achieves an impressive 97.96% accuracy in classifying deer antler slices and outperforms other related models. This approach can accurately differentiate between different types of deer antler slices and is particularly suitable for small-scale datasets. |
| first_indexed | 2024-03-11T23:37:13Z |
| format | Article |
| id | doaj.art-b8eac43bd08f4b59920168a80765b8a7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T23:37:13Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b8eac43bd08f4b59920168a80765b8a72023-09-19T23:02:03ZengIEEEIEEE Access2169-35362023-01-0111997059971510.1109/ACCESS.2023.329002610164254An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler SlicesDongming Li0https://orcid.org/0000-0001-7364-6070Rui Yao1https://orcid.org/0009-0000-3067-0425Chenglin Yang2Chunxi Zhao3https://orcid.org/0009-0008-8324-003XLijuan Zhang4College of Internet of Things Engineering, Wuxi University, Wuxi, ChinaCollege of Information Technology, Jilin Agricultural University, Changchun, ChinaCollege of Information Technology, Jilin Agricultural University, Changchun, ChinaCollege of Information Technology, Jilin Agricultural University, Changchun, ChinaCollege of Internet of Things Engineering, Wuxi University, Wuxi, ChinaDeer antler slices are highly valued in Chinese herbal medicine due to their medicinal properties. However, the current process for classifying these slices is time-consuming and subjective. To overcome this issue, we propose an intelligent classification and recognition model based on the Res2Net architecture. Our neural network utilizes an inverse bottleneck structure to enhance grouped convolution and reduce model parameters and computation time. Additionally, we integrate an improved grouped convolution into the Res2Net model and leverage the efficient channel attention (ECA) mechanism to improve feature extraction. Our model achieves an impressive 97.96% accuracy in classifying deer antler slices and outperforms other related models. This approach can accurately differentiate between different types of deer antler slices and is particularly suitable for small-scale datasets.https://ieeexplore.ieee.org/document/10164254/Attention mechanismdeer antler slicesfeature extractionimage processingdeep learningmulti-scale backbone networks |
| spellingShingle | Dongming Li Rui Yao Chenglin Yang Chunxi Zhao Lijuan Zhang An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices IEEE Access Attention mechanism deer antler slices feature extraction image processing deep learning multi-scale backbone networks |
| title | An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices |
| title_full | An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices |
| title_fullStr | An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices |
| title_full_unstemmed | An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices |
| title_short | An Improved Res2Net-Based Model for Classifying the Appearance of Deer Antler Slices |
| title_sort | improved res2net based model for classifying the appearance of deer antler slices |
| topic | Attention mechanism deer antler slices feature extraction image processing deep learning multi-scale backbone networks |
| url | https://ieeexplore.ieee.org/document/10164254/ |
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