Dasheng Wu
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View article: An Improved Lightweight Model for Protected Wildlife Detection in Camera Trap Images
An Improved Lightweight Model for Protected Wildlife Detection in Camera Trap Images Open
Effective monitoring of protected wildlife is crucial for biodiversity conservation. While camera traps provide valuable data for ecological observation, existing deep learning models often suffer from low accuracy in detecting rare specie…
View article: MSHLB-DETR: Transformer-Based Multi-Scale Citrus Huanglongbing Detection in Orchards with Aggregation Enhancement
MSHLB-DETR: Transformer-Based Multi-Scale Citrus Huanglongbing Detection in Orchards with Aggregation Enhancement Open
Detecting citrus Huanglongbing (HLB) in orchard environments is particularly challenging due to multi-scale targets and occlusions due to clustering, which manifest as complex and variable backgrounds, targets ranging from distant single l…
View article: SD-YOLOv8: SAM-Assisted Dual-Branch YOLOv8 Model for Tea Bud Detection on Optical Images
SD-YOLOv8: SAM-Assisted Dual-Branch YOLOv8 Model for Tea Bud Detection on Optical Images Open
It is challenging to achieve accurate tea bud detection in optical images with complex backgrounds since distinguishing between the foregrounds and backgrounds of these images remains difficult. Although several studies have been proposed …
View article: RLK-YOLOv8: multi-stage detection of strawberry fruits throughout the full growth cycle in greenhouses based on large kernel convolutions and improved YOLOv8
RLK-YOLOv8: multi-stage detection of strawberry fruits throughout the full growth cycle in greenhouses based on large kernel convolutions and improved YOLOv8 Open
Introduction In the context of intelligent strawberry cultivation, achieving multi-stage detection and yield estimation for strawberry fruits throughout their full growth cycle is essential for advancing intelligent management of greenhous…
View article: Regional Forest Carbon Stock Estimation Based on Multi-Source Data and Machine Learning Algorithms
Regional Forest Carbon Stock Estimation Based on Multi-Source Data and Machine Learning Algorithms Open
Accurately assessing forest carbon stock (FCS) is essential for analyzing its spatial distribution and gauging the capacity of forests to sequester carbon. This research introduces a novel approach for estimating FCS by integrating multipl…
View article: Tree Height Estimation of Chinese Fir Forests Based on Geographically Weighted Regression and Forest Survey Data
Tree Height Estimation of Chinese Fir Forests Based on Geographically Weighted Regression and Forest Survey Data Open
Estimating tree height at the national to regional scale is crucial for assessing forest health and forest carbon storage and understanding forest ecosystem processes. It also aids in formulating forest management and restoration policies …
View article: Pine wilt disease detection algorithm based on improved YOLOv5
Pine wilt disease detection algorithm based on improved YOLOv5 Open
Pine wilt disease (PWD) poses a significant threat to forests due to its high infectivity and lethality. The absence of an effective treatment underscores the importance of timely detection and isolation of infected trees for effective pre…
View article: Regional Forest Structure Evaluation Model Based on Remote Sensing and Field Survey Data
Regional Forest Structure Evaluation Model Based on Remote Sensing and Field Survey Data Open
The assessment of a forest’s structure is pivotal in guiding effective forest management, conservation efforts, and ensuring sustainable development. However, traditional evaluation methods often focus on isolated forest parameters and inc…
View article: TBC-YOLOv7: a refined YOLOv7-based algorithm for tea bud grading detection
TBC-YOLOv7: a refined YOLOv7-based algorithm for tea bud grading detection Open
Introduction Accurate grading identification of tea buds is a prerequisite for automated tea-picking based on machine vision system. However, current target detection algorithms face challenges in detecting tea bud grades in complex backgr…
View article: Assessment of Forest Ecological Function Levels Based on Multi-Source Data and Machine Learning
Assessment of Forest Ecological Function Levels Based on Multi-Source Data and Machine Learning Open
Forest ecological function is one of the key indicators reflecting the quality of forest resources. The traditional weighting method to assess forest ecological function is based on a large amount of ground survey data; it is accurate but …
View article: The Distributionally Robust Inventory Strategy of the Overconfident Retailer under Supply Uncertainty
The Distributionally Robust Inventory Strategy of the Overconfident Retailer under Supply Uncertainty Open
To factor in the retailer’s overconfidence when dealing with the inventory problem with supply uncertainty, this paper develops a distributionally robust optimization model by only considering the mean and variance of the yield rate distri…
View article: Detection of Chrysanthemums Inflorescence Based on Improved CR-YOLOv5s Algorithm
Detection of Chrysanthemums Inflorescence Based on Improved CR-YOLOv5s Algorithm Open
Accurate recognition of the flowering stage is a prerequisite for flower yield estimation. In order to improve the recognition accuracy based on the complex image background, such as flowers partially covered by leaves and flowers with ins…
View article: Comparison of Multiple Machine Learning Models for Estimating the Forest Growing Stock in Large-Scale Forests Using Multi-Source Data
Comparison of Multiple Machine Learning Models for Estimating the Forest Growing Stock in Large-Scale Forests Using Multi-Source Data Open
The forest growing stock is one of the key indicators in monitoring forest resources, and its quantitative estimation is of great significance. Based on multi-source data, including Sentinel-1 radar remote sensing data, Sentinel-2 optical …
View article: Comparison of Variable Selection Methods among Dominant Tree Species in Different Regions on Forest Stock Volume Estimation
Comparison of Variable Selection Methods among Dominant Tree Species in Different Regions on Forest Stock Volume Estimation Open
The forest stock volume (FSV) is one of the crucial indicators to reflect the quality of forest resources. Variable selection methods are usually used for FSV estimated models. However, few studies have explored which variable selection me…
View article: Deep Segmentation Feature-Based Radiomics Improves Recurrence Prediction of Hepatocellular Carcinoma
Deep Segmentation Feature-Based Radiomics Improves Recurrence Prediction of Hepatocellular Carcinoma Open
Objective and Impact Statement . This study developed and validated a deep semantic segmentation feature-based radiomics (DSFR) model based on preoperative contrast-enhanced computed tomography (CECT) combined with clinical information to …
View article: Estimation of DBH at Forest Stand Level Based on Multi-Parameters and Generalized Regression Neural Network
Estimation of DBH at Forest Stand Level Based on Multi-Parameters and Generalized Regression Neural Network Open
The diameter at breast height (DBH) is an important factor used to estimate important forestry indices like forest growing stock, basal area, biomass, and carbon stock. The traditional DBH ground surveys are time-consuming, labor-intensive…
View article: A Levenberg–Marquardt Backpropagation Neural Network for Predicting Forest Growing Stock Based on the Least-Squares Equation Fitting Parameters
A Levenberg–Marquardt Backpropagation Neural Network for Predicting Forest Growing Stock Based on the Least-Squares Equation Fitting Parameters Open
Traditional field surveys are expensive, time-consuming, laborious, and difficult to perform, especially in mountainous and dense forests, which imposes a burden on forest management personnel and researchers. This study focuses on predict…
View article: Dynamic Estimation of Forest Volume Based on Multi-Source Data and Neural Network Model
Dynamic Estimation of Forest Volume Based on Multi-Source Data and Neural Network Model Open
It is quite necessary to explore some more efficient and reliable estimation models which could integrate or, in some cases, substitute the traditional and expensive measuring techniques in forest resources management owing to the rising i…