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

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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An efficient strawberry segmentation model based on Mask R-CNN and TensorRT

Currently, artificial intelligence (AI), particularly computer vision (CV), has numerous applications in agriculture. In this field, the production and consumption of strawberries have experienced great...

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Precision agriculture technologies for soil site-specific nutrient management: A comprehensive review

Amidst the growing food demands of an increasing population, agricultural intensification frequently depends on excessive chemical and fertilizer applications. While this approach initially boosts crop...

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Addressing computation resource exhaustion associated with deep learning training of three-dimensional hyperspectral images using multiclass weed classification

Addressing the computational bottleneck of training deep learning models on high-resolution, three-dimensional images, this study introduces an optimized approach, combining distributed learning (parallelism),...

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Advancing precision agriculture: A comparative analysis of YOLOv8 for multi-class weed detection in cotton cultivation

Effective weed management plays a critical role in enhancing the productivity and sustainability of cotton cultivation. The rapid emergence of herbicide-resistant weeds has underscored the need for...

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Deep learning-based classification, detection, and segmentation of tomato leaf diseases: A state-of-the-art review

The early identification and treatment of tomato leaf diseases are crucial for optimizing plant productivity, efficiency and quality. Misdiagnosis by the farmers poses the risk of inadequate treatments,...

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Using UAV-based multispectral images and CGS-YOLO algorithm to distinguish maize seeding from weed

Accurate recognition of maize seedlings on the plot scale under the disturbance of weeds is crucial for early seedling replenishment and weed removal. Currently, UAV-based maize seedling recognition...

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Prediction of sugar beet yield and quality parameters using Stacked-LSTM model with pre-harvest UAV time series data and meteorological factors

Accurate pre-harvest prediction of sugar beet yield is vital for effective agricultural management and decision-making. However, traditional methods are constrained by reliance on empirical knowledge,...

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A review of the application prospects of cloud-edge-end collaborative technology in freshwater aquaculture

This paper reviews the application and potential of cloud-edge-end collaborative (CEEC) technology in the field of freshwater aquaculture, a rapidly developing sector driven by the growing global demand...

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TGFN-SD: A text-guided multimodal fusion network for swine disease diagnosis

China is the world's largest producer of pigs, but traditional manual prevention, treatment, and diagnosis methods cannot satisfy the demands of the current intensive production environment. Existing...

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Digitalizing greenhouse trials: An automated approach for efficient and objective assessment of plant damage using deep learning

The use of image based and, recently, deep learning-based systems have provided good results in several applications. Greenhouse trials are key part in the process of developing and testing new herbicides...

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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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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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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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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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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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Fast extraction of navigation line and crop position based on LiDAR for cabbage crops

This paper describes the design, algorithm development, and experimental verification of a precise spray perception system based on LiDAR were presented to address the issue that the navigation line...

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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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Classifying early apple scab infections in multispectral imagery using convolutional neural networks

Multispectral imaging systems combined with deep learning classification models can be cost-effective tools for the early detection of apple scab (Venturia inaequalis) disease in commercial orchards....

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Robotization of banana de-handing under multi-constraint scenarios: Challenges and future directions

Banana de-handing is an important part of banana post-harvesting operation. The traditional artificial de-handing model has problems such as labor intensity, inaccurate cutting, uneven cutting surface,...

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