-
1761
WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification
Published 2025-07-01“…Our research evaluates several state-of-the-art object detection architectures, including DINO Transformer (with ResNet-101 and Swin backbones), Detection Transformer (DETR), EfficientNet B4, YOLO v8, and RetinaNet. …”
Get full text
Article -
1762
Dual Improvements DCNv4 and AsDDet Mechanisms for Small Object Detection in Aerial Imagery
Published 2025-01-01“…This study introduces a dual enhancement mechanism integrating Deformable Convolution v4 (DCNv4) and an Asymmetric Decoupled Detection Head (AsDDet) to significantly improve the detection performance of small objects in high-altitude unmanned aerial vehicle (UAV) imagery using YOLOv11 model architecture. …”
Get full text
Article -
1763
Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region
Published 2025-02-01“…Balancing between model detection performance and efficiency poses many challenges. …”
Get full text
Article -
1764
YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping
Published 2025-07-01“…To address the issues of low efficiency and large errors in traditional manual cucumber fruit phenotyping methods, this paper proposes the application of keypoint detection technology for cucumber phenotyping and designs an improved lightweight model called YOLO11m-SCFPose. …”
Get full text
Article -
1765
-
1766
An MSRE-Assisted Glycerol-Enhanced RPA-CRISPR/Cas12a Method for Methylation Detection
Published 2024-12-01“…Conventional methylation detection methods relying on bisulfite conversion have limitations such as time-consuming, complex processes and sample degradation; thus, a more rapid and efficient method is needed. …”
Get full text
Article -
1767
Machine learning-based model for acute asthma exacerbation detection using routine blood parameters
Published 2025-07-01“…Conclusions: This machine learning model provides an efficient and practical tool for detecting AAE using routine blood parameters, offering potential value in clinical practice, especially in resource-limited settings. …”
Get full text
Article -
1768
Star-YOLO: A Lightweight Real-Time Wheat Grain Detection Model for Embedded Deployment
Published 2025-01-01“…With the rapid advancement of precision agriculture, traditional object detection algorithms struggle with limited efficiency and accuracy in wheat grain detection and counting, while the need for real-time deployment of deep learning models on embedded devices becomes increasingly critical. …”
Get full text
Article -
1769
EER-DETR: An Improved Method for Detecting Defects on the Surface of Solar Panels Based on RT-DETR
Published 2025-05-01“…In the context of the rapid popularization of clean energy, the precise identification of surface defects on photovoltaic modules has become a core technical bottleneck limiting the operational efficiency of power stations. In response to the shortcomings of existing detection methods in identifying tiny defects and model efficiency, this study innovatively constructed the EER-DETR detection framework: firstly, a feature reconstruction module WDBB with a differentiable branch structure was introduced to significantly enhance the feature retention ability for fine cracks and other small targets; secondly, an adaptive feature pyramid network EHFPN was innovatively designed, which achieved efficient integration of multi-level features through a dynamic weight allocation mechanism, reducing the model complexity by 9.7% while maintaining detection accuracy, solving the industry problem of “precision—efficiency imbalance” in traditional feature pyramid networks; finally, an enhanced upsampling component was introduced to effectively address the problem of detail loss that occurs in traditional methods during image resolution enhancement. …”
Get full text
Article -
1770
Intelligent single-cell manipulation: LLMs- and object detection-enhanced active-matrix digital microfluidics
Published 2025-07-01“…By combining this with a fully programmable lab-on-a-chip system, we present a breakthrough for SCSM by combining LLMs and object detection technologies. With the proposed platform, the single-cell sample generation rate and identification precision reach up to 25% and 98%, respectively, which are much higher than the existing platforms in terms of SCSM efficiency and performance. …”
Get full text
Article -
1771
Technical note: Flow cytometry assays for the detection, counting and cell sorting of polyphosphate-accumulating bacteria
Published 2025-04-01“…The potential of flow cytometry to quantify and sort polyphosphate-accumulating bacteria in complex environmental samples, including soil, freshwater and sediments, was also examined. …”
Get full text
Article -
1772
BCS_YOLO: Research on Corn Leaf Disease and Pest Detection Based on YOLOv11n
Published 2025-07-01“…Frequent corn leaf diseases and pests pose serious threats to agricultural production. Traditional manual detection methods suffer from significant limitations in both performance and efficiency. …”
Get full text
Article -
1773
A Tactical Conflict Detection and Resolution Method for En Route Conflicts in Trajectory-Based Operations
Published 2022-01-01“…In the conflict detection (CD) submodule, a spatial data structure with low time complexity, the R tree algorithm, is used. …”
Get full text
Article -
1774
Immobilization of DNA Aptamers on Polyester Cloth for Antigen Detection by Dot Blot Immunoenzymatic Assay (Aptablot)
Published 2013-01-01“…A simple dot blot immunoenzymatic assay system was developed using polyester cloth coated with an oligo-DNA aptamer to provide a high-affinity macroporous surface for the efficient capture of a model protein analyte (thrombin) in complex sample matrices such as foods. …”
Get full text
Article -
1775
MA-YOLO: A Pest Target Detection Algorithm with Multi-Scale Fusion and Attention Mechanism
Published 2025-06-01“…To address the high computational complexity and inadequate feature representation in traditional convolutional networks, this study proposes MA-YOLO, an agricultural pest detection model based on multi-scale fusion and attention mechanisms. …”
Get full text
Article -
1776
High resolution remote sensing image object detection algorithm based on improved YOLOv8
Published 2025-01-01“…In view of problems such as objects are interfered by complex background, objects are small and densely distributed, objects are multi-scale and their directions are random in high resolution remote sensing image data, an object detection algorithm for high resolution remote sensing image based on improved YOLOv8 was proposed. …”
Get full text
Article -
1777
Feature Multi-Scale Enhancement and Adaptive Dynamic Fusion Network for Infrared Small Target Detection
Published 2025-04-01“…This study aims to address a series of challenges in infrared small target detection, particularly in complex backgrounds and high-noise environments. …”
Get full text
Article -
1778
Quantifying solid volume of stacked eucalypt timber using detection-segmentation and diameter distribution models
Published 2024-12-01“…This procedure, which integrates automatic log detection with diameter distribution models, offers a scalable solution applicable to large and complex timber stacks. …”
Get full text
Article -
1779
Enhanced Cloud Detection Using a Unified Multimodal Data Fusion Approach in Remote Images
Published 2025-04-01“…Aiming at the complexity of network architecture design and the low computational efficiency caused by variations in the number of modalities in multimodal cloud detection tasks, this paper proposes an efficient and unified multimodal cloud detection model, M2Cloud, which can process any number of modal data. …”
Get full text
Article -
1780
Incentivising cooperation by judging a group’s performance by its weakest member in neuroevolution and reinforcement learning
Published 2025-07-01“…Notably, the introduced approach improves overall efficiency, as equitably-minded agents collectively achieve greater stability and higher individual outcomes than agents pursuing purely selfish strategies.DiscussionThis methodology aligns closely with biological mechanisms observed in nature, specifically group-level selection and inclusive fitness theory. …”
Get full text
Article