AI RESEARCH
PestVL-Net: Enabling Multimodal Pest Learning via Fine-grained Vision-Language Interaction
arXiv CS.CV
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ArXi:2604.17278v1 Announce Type: new Effective pest recognition and management are crucial for sustainable agricultural development. However, collecting pest data in real scenarios is often challenging. Compared to other domains, pests exhibit a wide variety of species with complex and diverse morphological characteristics. Existing techniques struggle to effectively model the key visual and high-level semantic features of pests in a fine-grained manner. These limitations hinder the practical application of such methods in real agricultural scenarios.