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ISSN: 2589-7217
CN: 10-1795/S
p-ISSN: 2097-2113

Multi-scale cross-modal feature fusion and cost-sensitive loss function for differential detection of occluded bagging pears in practical orchards

In practical orchards, the challenges posed by fruit overlapping, branch and leaf occlusion, significantly impede the successful implementation of automated picking, particularly for bagging pears....

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ADeepWeeD: An adaptive deep learning framework for weed species classification

Efficient weed management in agricultural fields is essential for attaining optimal crop yields and safeguarding global food security. Every year, farmers worldwide invest significant time, capital,...

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Technical study on the efficiency and models of weed control methods using unmanned ground vehicles: A review

As precision agriculture evolves, unmanned ground vehicles (UGVs) have become an essential tool for improving weed management techniques, offering automated and targeted methods that obviously reduce...

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An autonomous navigation method for field phenotyping robot based on ground-air collaboration

High-throughput phenotyping collection technology is important in affecting the efficiency of crop breeding. This study introduces a novel autonomous navigation method for phenotyping robots that leverages...

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MSNet: A multispectral-image driven rapeseed canopy instance segmentation network

Precise detection of rapeseed and the growth of its canopy area are crucial phenotypic indicators of its growth status. Achieving accurate identification of the rapeseed target and its growth region...

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PWM offline variable application based on UAV remote sensing 3D prescription map

Precision application in orchards enhancing deposition uniformity and environmental sustainability by accurately matching nozzle output with canopy parameters. This study provides a pipeline for creating...

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AI-driven aquaculture: A review of technological innovations and their sustainable impacts

The integration of artificial intelligence (AI) in aquaculture has been identified as a transformative force, enhancing various operational aspects from water quality management to genetic optimization....

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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality

Seeds are essential to the agri-food industry. However, their quality is vulnerable to biotic and abiotic stresses during production and storage, leading to various types of deterioration. Real-time...

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Stereo vision based broccoli recognition and attitude estimation method for field harvesting

At present, automatic broccoli harvest in field still faces some issues. It is difficult to segment broccoli in real time under complex field background, and hard to pick tilt-growing broccoli for the...

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Boosting grapevine phenological stages prediction based on climatic data by pseudo-labeling approach

Predicting grapevine phenological stages (GPHS) is critical for precisely managing vineyard operations, including plant disease treatments, pruning, and harvest. Solutions commonly used to address viticulture...

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Unveiling the drivers contributing to global wheat yield shocks through quantile regression

Sudden reductions in crop yield (i.e., yield shocks) severely disrupt the food supply, intensify food insecurity, depress farmers' welfare, and worsen a country's economic conditions. Here, we study...

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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques

To reduce damage caused by insect pests, farmers use insecticides to protect produce from crop pests. This practice leads to high synthetic chemical usage because a large portion of the applied insecticide...

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Navigating challenges/opportunities in developing smart agricultural extension platforms: Multi-media data mining techniques

Agricultural Extension (AE) research faces significant challenges in producing relevant and practical knowledge due to rapid advancements in artificial intelligence (AI). AE struggles to keep pace with...

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Transformer-based audio-visual multimodal fusion for fine-grained recognition of individual sow nursing behaviour

Nursing behaviour and the calling-to-nurse sound are crucial indicators for assessing sow maternal behaviour and nursing status. However, accurately identifying these behaviours for individual sows...

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Effective methods for mitigate the impact of light occlusion on the accuracy of online cabbage recognition in open fields

To address the low recognition accuracy of open-field vegetables under light occlusion, this study focused on cabbage and developed an online target recognition model based on deep learning. Using Yolov8n...

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Assessing particle application in multi-pass overlapping scenarios with variable rate centrifugal fertilizer spreaders for precision agriculture

Environmental impacts and economic demands are driving the development of variable rate fertilization (VRF) technology for precision agriculture. Despite the advantages of a simple structure, low cost...

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Joint optimization of AI large and small models for surface temperature and emissivity retrieval using knowledge distillation

The rapid advancement of artificial intelligence in domains such as natural language processing has catalyzed AI research across various fields. This study introduces a novel strategy, the AutoKeras-Knowledge...

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Multimodal behavior recognition for dairy cow digital twin construction under incomplete modalities: A modality mapping completion network approach

The recognition of dairy cow behavior is essential for enhancing health management, reproductive efficiency, production performance, and animal welfare. This paper addresses the challenge of modality...

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Mapping of soil sampling sites using terrain and hydrological attributes

Efficient soil sampling is essential for effective soil management and research on soil health. Traditional site selection methods are labor-intensive and fail to capture soil variability comprehensively....

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Enhancing maize LAI estimation accuracy using unmanned aerial vehicle remote sensing and deep learning techniques

The leaf area index (LAI) is crucial for precision agriculture management. UAV remote sensing technology has been widely applied for LAI estimation. Although spectral features are widely used for LAI...

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Research on an orchard row centreline multipoint autonomous navigation method based on LiDAR

Orchard intelligent equipment must perform autonomous navigation tasks along fruit tree row centrelines and headlands according to established operational requirements. The tree canopy obstructs satellite...

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Comprehensive review on 3D point cloud segmentation in plants

Segmentation of three-dimensional (3D) point clouds is fundamental in comprehending unstructured structural and morphological data. It plays a critical role in research related to plant phenomics, 3D...

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Identifying key factors influencing maize stalk lodging resistance through wind tunnel simulations with machine learning algorithms

Climate change has intensified maize stalk lodging, severely impacting global maize production. While numerous traits influence stalk lodging resistance, their relative importance remains unclear, hindering...

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Automatic body condition scoring system for dairy cows in group state based on improved YOLOv5 and video analysis

This study proposes an automated scoring system for cow body condition using improved YOLOv5 to assess the body condition distribution of herd cows, which significantly impacts herd productivity and...

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Efficient one-stage detection of shrimp larvae in complex aquaculture scenarios

The swift evolution of deep learning has greatly benefited the field of intensive aquaculture. Specifically, deep learning-based shrimp larvae detection has offered important technical assistance for...

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