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PineSight: The Model Improving Pine Wilt Disease Detection in Low-Light Environments

https://doi.org/10.2139/ssrn.5600429
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inferredcites →https://doi.org/10.1007/978-981-19-3387-5_152openalex-snapshot
A Monitoring Scheme for Pine Wood Nematode Disease Tree Based on Deep Learning and Ground Monitoring
inferredcites →https://doi.org/10.1007/s11676-021-01423-8openalex-snapshot
Surveillance of pine wilt disease by high resolution satellite
inferredcites →https://doi.org/10.1016/j.compag.2024.108671openalex-snapshot
Exploring the potential of visual tracking and counting for trees infected with pine wilt disease based on improved YOLOv5 and StrongSORT algorithm
inferredcites →https://doi.org/10.1016/j.compag.2024.108690openalex-snapshot
Harnessing synthetic data for enhanced detection of Pine Wilt Disease: An image classification approach
inferredcites →https://doi.org/10.1016/j.ecolind.2023.111215openalex-snapshot
An efficient approach to monitoring pine wilt disease severity based on random sampling plots and UAV imagery
inferredcites →https://doi.org/10.1016/j.ecolind.2024.112764openalex-snapshot
Detection of pine wilt disease infected pine trees using YOLOv5 optimized by attention mechanisms and loss functions
inferredcites →https://doi.org/10.1016/j.foreco.2021.119890openalex-snapshot
A multi-point aggregation trend of the outbreak of pine wilt disease in China over the past 20 years
inferredcites →https://doi.org/10.1016/j.foreco.2022.120677openalex-snapshot
Ensemble evaluation of the spatial distribution of pine wilt disease mediated by insect vectors in South Korea
inferredcites →https://doi.org/10.1016/j.image.2022.116848openalex-snapshot
Comparing deep learning models for low-light natural scene image enhancement and their impact on object detection and classification: Overview, empirical evaluation, and challenges
inferredcites →https://doi.org/10.1016/j.scitotenv.2023.167075openalex-snapshot
Risk assessment framework for pine wilt disease: Estimating the introduction pathways and multispecies interactions among the pine wood nematode, its insect vectors, and hosts in China
inferredcites →https://doi.org/10.1038/s41598-020-79653-9openalex-snapshot
Explainable identification and mapping of trees using UAV RGB image and deep learning
inferredcites →https://doi.org/10.1080/01431161.2024.2339192openalex-snapshot
Mapping large-scale pine wilt disease trees with a lightweight deep-learning model and very high-resolution UAV images
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00185openalex-snapshot
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01042openalex-snapshot
Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00555openalex-snapshot
Toward Fast, Flexible, and Robust Low-Light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01386openalex-snapshot
EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention
inferredcites →https://doi.org/10.1109/iccsse59359.2023.10245235openalex-snapshot
Automatic Image Screening of Pine Wilt Disease Based on TransUNet
inferredcites →https://doi.org/10.1109/iccv.2019.00310openalex-snapshot
CARAFE: Content-Aware ReAssembly of FEatures
inferredcites →https://doi.org/10.1109/iccv51070.2023.00743openalex-snapshot
Iterative Prompt Learning for Unsupervised Backlit Image Enhancement
inferredcites →https://doi.org/10.1109/iicaiet62352.2024.10730072openalex-snapshot
Unmanned Aerial Vehicle-Enabled Deep-Learning Based Detection and Segmentation
inferredcites →https://doi.org/10.1109/jstars.2024.3478333openalex-snapshot
Detection of Pine Wilt Disease Using AAV Remote Sensing With an Improved YOLO Model
inferredcites →https://doi.org/10.1111/ppa.13875openalex-snapshot
Pine wilt disease: A global threat to forestry
inferredcites →https://doi.org/10.1186/s12870-024-04771-9openalex-snapshot
Pine wilt disease: what do we know from proteomics?
inferredcites →https://doi.org/10.3389/fpls.2024.1381367openalex-snapshot
Large field-of-view pine wilt disease tree detection based on improved YOLO v4 model with UAV images
inferredcites →https://doi.org/10.3390/drones6110353openalex-snapshot
A Global Multi-Scale Channel Adaptation Network for Pine Wilt Disease Tree Detection on UAV Imagery by Circle Sampling
inferredcites →https://doi.org/10.3390/f14020174openalex-snapshot
Pine Wilt Disease in Northeast and Northwest China: A Comprehensive Risk Review
inferredcites →https://doi.org/10.3390/f14030588openalex-snapshot
Identification of Pine Wilt Disease Infected Wood Using UAV RGB Imagery and Improved YOLOv5 Models Integrated with Attention Mechanisms
inferredcites →https://doi.org/10.3390/f14081687openalex-snapshot
Habitat Suitability of Pine Wilt Disease in Northeast China under Climate Change Scenario
inferredcites →https://doi.org/10.3390/f15040691openalex-snapshot
Detection of Pine-Wilt-Disease-Affected Trees Based on Improved YOLO v7
inferredcites →https://doi.org/10.3390/f15050737openalex-snapshot
Pine-YOLO: A Method for Detecting Pine Wilt Disease in Unmanned Aerial Vehicle Remote Sensing Images
inferredcites →https://doi.org/10.3390/f15122147openalex-snapshot
Advances in Global Remote Sensing Monitoring of Discolored Pine Trees Caused by Pine Wilt Disease: Platforms, Methods, and Future Directions
inferredcites →https://doi.org/10.3390/ijms231810797openalex-snapshot
The Detection of Pine Wilt Disease: A Literature Review
inferredcites →https://doi.org/10.3390/rs15020360openalex-snapshot
Remote Sensing Monitoring of Pine Wilt Disease Based on Time-Series Remote Sensing Index
inferredcites →https://doi.org/10.3390/s20133729openalex-snapshot
Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
inferredcites →https://doi.org/10.34133/plantphenomics.0129openalex-snapshot
Exploring the Close-Range Detection of UAV-Based Images on Pine Wilt Disease by an Improved Deep Learning Method
inferredcites →https://doi.org/10.55014/pij.v7i1.505openalex-snapshot
The occurrence and comprehensive control technology of pine wilt disease
inferredcites →https://doi.org/10.7780/kjrs.2019.35.3.2openalex-snapshot
Detection of Damaged Pine Tree by the Pine Wilt Disease Using UAV Image
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