Multimodal weed infestation rate prediction framework for efficient farmland management

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 235, P. 110294 - 110294

Published: March 30, 2025

Language: Английский

PlanText: Gradually Masked Guidance to Align Image Phenotype with Trait Description for Plant Disease Texts

Plant Phenomics, Journal Year: 2024, Volume and Issue: 6

Published: Jan. 1, 2024

Plant diseases are a critical driver of the global food crisis. The integration advanced artificial intelligence technologies can substantially enhance plant disease diagnostics. However, current methods for early and complex detection remain challenging. Employing multimodal technologies, akin to medical diagnostics that combine diverse data types, may offer more effective solution. Presently, reliance on single-modal predominates in research, which limits scope detailed diagnosis. Consequently, developing text modality generation techniques is essential overcoming limitations recognition. To this end, we propose method aligning phenotypes with trait descriptions, diagnoses by progressively masking images. First, training validation, annotate 5,728 phenotype images expert diagnostic provide annotated labels 210,000 Then, PhenoTrait description model, consists heterogeneous feature encoders as well switching-attention decoders, accurate context-aware output. Next, generate phenotypically appropriate description, adopt 3 stages embedding image features into semantic structures, characterizations preserve features. Finally, our experimental results show model outperforms several frontier models multiple including larger GPT-4 GPT-4o. Our code dataset available at https://plantext.samlab.cn/.

Language: Английский

Self-powered flexible sensor network for continuous monitoring of crop micro-environment and growth states

Measurement, Journal Year: 2024, Volume and Issue: 242, P. 116002 - 116002

Published: Oct. 18, 2024

Language: Английский