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Pest image recognition algorithm based on joint adversarial transfer learning
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DOI：10.1016/j.measurement.2026.121620.png)
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摘要
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• 构建了一个面向迁移学习的害虫数据集（Pest-TL），包含20个农业和林业害虫类别。• 提出了一种联合对抗迁移学习框架，用于鲁棒跨域害虫图像识别。• 引入中心感知约束，以在领域漂移下增强判别特征学习。• 设计了相关性对齐约束，以减少跨域特征分布差异。
Keyword:
pest image recognition
transfer learning
adversarial learning
domain adaptation
feature extraction
期刊
IF:
5.6
论文数:
2.0W
被引数:
5.4W
机构
引用论文
Sun, H.; Chu, H.Q.; Qin, Y.M.; Hu, P.; Wang, R.F. Empowering Smart Soybean Farming with Deep Learning: Progress, Challenges, and Future Perspectives. Agronomy 2025, 15, 1831. [Google Scholar] [CrossRef]Sun, H.; Chu, H.Q.; Qin, Y.M.; Hu, P.; Wang, R.F. 利用深度学习赋能智能大豆种植：进展、挑战与未来展望. Agronomy 2025, 15, 1831. [Google Scholar] [CrossRef].png)
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