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881
Subsea Nodule Recognition and Deployment Detection Method Based on Improved YOLOv8s
Published 2025-01-01“…An improved small-target detection model based on YOLOv8s is proposed to address the challenges associated with deep-sea polymetallic nodule detection, such as complex target shapes, small sizes, and strong environmental interference. …”
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882
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883
Integrating ANN and ANFIS for effective fault detection and location in modern power grid
Published 2025-01-01“…The increasing complexity and demand for reliability in modern power systems necessitate advanced techniques for fault detection, classification, and location. …”
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884
Lightweight Small Target Detection Algorithm Based on YOLOv8 Network Improvement
Published 2025-01-01“…The modules have been designed to optimise feature extraction and improve model efficiency. The paper also discusses the challenges associated with low accuracy in small target detection and high model complexity in UAV applications. …”
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885
Intelligent Casting Quality Inspection Method Integrating Anomaly Detection and Semantic Segmentation
Published 2025-04-01“…Customized optical path design is often required, especially when conducting internal and external defect inspections, which increases overall operational complexity and reduces inspection efficiency. We developed an automated optical inspection (AOI) system to address these challenges. …”
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886
Quantitative Detection of Water Content of Winter Jujubes Based on Spectral Morphological Features
Published 2025-02-01“…The spectral information extracted from hyperspectral images is characterized by redundancy and complexity, while the spectral morphological features extracted from the spectral information help to simplify the data and provide rich information about the material composition. …”
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887
Application of the YOLOv11-seg algorithm for AI-based landslide detection and recognition
Published 2025-04-01“…Compared with traditional methods, YOLOv11-seg performs better in detecting complex boundaries and handling occlusion, demonstrating superior detection accuracy and segmentation quality. …”
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888
Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture
Published 2024-12-01“…This model provides technical support for Xinli No. 7 fruit detection and model deployment in complex environments.…”
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889
ITD-YOLO: An Improved YOLO Model for Impurities in Premium Green Tea Detection
Published 2025-04-01“…To solve this technical problem in the industry, this article proposes a lightweight algorithm for detecting and sorting impurities in premium green tea in order to improve sorting efficiency and reduce labor intensity. …”
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890
Outlier detection algorithm based on fast density peak clustering outlier factor
Published 2022-10-01“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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891
Outlier detection algorithm based on fast density peak clustering outlier factor
Published 2022-10-01“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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892
Single-Frame Infrared Target Detection Based on Fast Content-Related Modeling
Published 2025-01-01“…Most of methods mainly concentrate on modeling global features, overlooking the variations in local features due to complex scenes. To solve these problems, a single-frame infrared target detection method based on fast content-related modeling is proposed to combine global and local features of infrared images, describing the common features of varying scenes robustly and enhancing the distinction between targets and backgrounds. …”
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893
Intra‐ and interobserver reproducibility of transvaginal ultrasound for the detection and measurement of endometriotic lesions of the bowel
Published 2023-10-01“…Abstract Introduction The number and invasion depth of endometriotic bowel lesions, total length of bowel affected by endometriosis, lesion‐to‐anal verge distance, and extent of pouch of Douglas obliteration are important factors in preoperatively determining risk and complexity of endometriosis surgery. The intra‐ and interobserver reproducibility of transvaginal ultrasound in the evaluation of many of these parameters has not yet been investigated. …”
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894
Towards real-time interest point detection and description for mobile and robotic devices
Published 2024-09-01“…This paper demonstrates how techniques, developed for other CNN use cases, can be integrated into interest point detection and description systems to compress their network size and reduce the computational complexity; this reduces the barrier to their uptake in computationally challenged environments. …”
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895
Quantum Edge Detection and Convolution Using Paired Transform-Based Image Representation
Published 2025-03-01“…Classical edge detection algorithms often struggle to process large, high-resolution image datasets efficiently. …”
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896
Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks
Published 2024-11-01“…Despite the small difference in accuracy, Decision Tree demonstrated faster prediction times, making it more efficient for time-sensitive applications. This research concludes that while Random Forest provides higher accuracy for complex datasets, Decision Tree offers a more time-efficient solution with comparable accuracy.…”
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897
A hybrid Bi-LSTM and RBM approach for advanced underwater object detection.
Published 2024-01-01“…This research addresses the imperative need for efficient underwater exploration in the domain of deep-sea resource development, highlighting the importance of autonomous operations to mitigate the challenges posed by high-stress underwater environments. …”
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898
A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems
Published 2025-04-01“…However, the direct integration of anomaly detection within such a system is complex due to the wide variety of hardware used, different communication protocols, and given industrial requirements. …”
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899
Real-time classroom student behavior detection based on improved YOLOv8s
Published 2025-04-01“…However, the field still faces specific challenges, primarily concerning the accuracy of identifying student behaviors within complex and variable classroom environments, as well as the real-time capabilities of detection algorithms. …”
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900
3D Object Detection Based on Graph Network Fusion Sampling Strategy
Published 2025-04-01“…In the 3D target detection technology based on point cloud, there are problems like high cost of point cloud calculation and large gap between target scales, which lead to low target detection efficiency. …”
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