Wenjiang Huang

A physics-informed hybrid deep learning model for spatiotemporal rice disease prediction using multi-source data

Zichao Jin, Jiaoru Wang, Wenjiang Huang, Jingcheng Zhang et autres

Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework. Accordingly, we propose a physics-informed …

gb, cn (code pays fourni par la source)

Wheat stripe rust monitoring based on weighted multi-temporal features from UAV multispectral imagery under field conditions

Chao Ruan, Zhi Cao, Zheng Li, Shizhou Du et autres

Wheat stripe rust is a destructive airborne disease that requires timely field-scale monitoring. However, unmanned aerial vehicle (UAV) studies often use single-date imagery or fixed bi-temporal normalised difference (DN) features, overlooking unequal contributions from observation dates during symptom development. This study proposed …

cn (code pays fourni par la source)

Biological invasions Erode China's forest carbon stocks: Spatiotemporal expansion and edge preferences of Pine Wilt Disease

Bohai Hu, Wenjiang Huang, Zhuoqing Hao, Jing Guo et autres

cn (code pays fourni par la source)

Physics-Informed Transfer Learning Reduces Simulation to Reality Gaps for Winter Wheat Traits Retrieval from Hyperspectral Observations

Qi Sun, Quanjun Jiao, Shiyan Chen, Lulu Pan et autres

Accurate retrieval of crop structural and physiological traits from remote sensing data remains challenging due to limited field observations and poor cross-platform generalization of data-driven models. This study develops a physics-informed transfer learning framework to quantify the contributions of improving simulated data …

PCMTRefer: Symmetry-Aware Text-Guided Point Mamba for Referring Segmentation in Indoor 3D Point Clouds

Li Yuan, Bo Kong, Chenhao Li, Anting Guo et autres

Indoor 3D referring segmentation aims to identify and segment the target object in a point cloud according to a natural language expression. Although recent advances in multimodal feature fusion have markedly improved this task, existing methods do not jointly model the structural …

cn (code pays fourni par la source)

Precise Geometric-Priors-Guided 3D Point Cloud Segmentation Network for Auricle Region: GeoPriors-3DEarSeg

Li Yuan, Wenhao Zuo, Anting Guo, Wenjiang Huang

This paper addresses the core challenges in the 3D point cloud segmentation of the human auricle region, including the low distinguishability of weak-boundary features, the lack of anatomical priors in existing methods, the tendency of boundary features to be overwhelmed by background …

cn (code pays fourni par la source)

Remote Sensing for Early Detection of Pine Wilt Disease (From Bursaphelenchus xylophilus ): A critical review

Run Yu, Yelu Zeng, Z Y Li, Huaguo Huang et autres

cn (code pays fourni par la source)

Disease-specific Spectral Indices Enable Cross-Scale Monitoring of Wheat Stripe Rust From Leaf to Satellite Scales

Kehui Ren, Binxiang Qian, Chao Ruan, Anting Guo et autres

cn (code pays fourni par la source)

A two-step approach mitigates phenological influences and improves the reliability of wheat stripe rust detection and disease index estimation

Kehui Ren, Binxiang Qian, Chao Ruan, Jun Gao et autres

cn (code pays fourni par la source)

PPBM-YOLO: A lightweight and accurate detection model for multi-species airborne spores in wheat disease Cross-Infection scenarios

Yang Chen, Jinling Zhao, Xue Yang, Chunchun Li et autres

cn (code pays fourni par la source)

Monitoring of rubber tree powdery mildew by combining spatial-spectral features and plant traits quantified from UAV hyperspectral imagery

Xiangzhe Cheng, Wenjiang Huang, Anting Guo, Zhiying Cai et autres

Powdery mildew is a major disease affecting rubber tree yield. Rapid and accurate monitoring of this disease is crucial for plantation management. Previous studies have focused on spectral and spatial data for monitoring powdery mildew but have not adequately addressed the underlying …

cn, us (code pays fourni par la source)

Inversion of plant functional traits from hyperspectral imagery enhances the distinction of wheat stripe rust severity

Kehui Ren, Anting Guo, Binxiang Qian, Chao Ruan et autres