Tobacco leaf disease hole detection method based on spectral–spatial fusion multimodal transformer

Industrial Crops and Products 2026 Open access

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Authors: Jie Zhang, Zhanhao Zhang, Dayong Xu, Jiakang Li, Hongfu Zhu, Duanfei Wang, Ruidong Li, Jinsong Du, Fengxian Wang
DOI: 10.1016/j.indcrop.2026.123538
Cited by: 1
References: 27

Abstract

• Developed a CNN-Transformer dual-branch network for multi-modal tobacco defect detection. • Designed an adaptive fusion mechanism to enhance cross-modal feature consistency. • Built a dynamic detection framework to improve small lesion localization. • Introduced a multi-scale loss function to optimize learning for small targets.

Fields of Study & Subjects

Smart Agriculture and AI Water Quality Monitoring and Analysis Plant Surface Properties and Treatments

Publication details

Journal / source
Industrial Crops and Products
Publisher
Elsevier BV
Volume
248
Pages
123538–123538
Publication date
28 May 2026
Language
EN