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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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Abstract
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• A transfer-learning-oriented pest dataset (Pest-TL) with 20 agricultural and forestry pest categories is constructed. • A joint adversarial transfer learning framework is proposed for robust cross-domain pest image recognition. • A center-aware constraint is introduced to enhance discriminative feature learning under domain shifts. • A correlation alignment constraint is designed to reduce cross-domain feature distribution discrepancies.
Keywords:
pest image recognition
transfer learning
adversarial learning
domain adaptation
feature extraction
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5.6
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