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Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading
Published 2021-08-01“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
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363
Brain tumor detection through image fusion using whale optimization and edge preserving filter
Published 2025-03-01Get full text
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364
Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections
Published 2025-05-01Get full text
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365
LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning
Published 2024-01-01“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
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366
Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring
Published 2022-11-01“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
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367
AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11.
Published 2025-01-01“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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368
CSW-YOLO: A traffic sign small target detection algorithm based on YOLOv8.
Published 2025-01-01“…First, the bottleneck of the C2f module in the original yolov8 network is replaced with the residual Faster-Block module in FasterNet, and then the new channel mixer convolution GLU (CGLU) in TransNeXt is combined with it to construct the C2f-faster-CGLU module, reducing the number of model parameters and computational load; Secondly, the SPPF module is combined with the large separable kernel attention (LSKA) to construct the SPPF-LSKA module, which greatly enhances the feature extraction ability of the model; Then, by adding a small target detection layer, the accuracy of small target detection such as traffic signs is greatly improved; Finally, the Inner-IoU and MPDIoU loss functions are integrated to construct WISE-Inner-MPDIoU, which replaces the original CIoU loss function, thereby improving the calculation accuracy. …”
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369
VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes
Published 2025-01-01“…Accurate detection of vulnerable road users (VRUs) is critical for enhancing traffic safety and advancing autonomous driving systems. …”
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370
DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK
Published 2025-06-01“…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
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371
DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection
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372
TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5
Published 2025-05-01“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
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373
YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes
Published 2025-04-01“…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
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374
Asynchronous bearing only tracking management approach in distributed multi-function integrated sensors
Published 2024-12-01“…The distributed multi-function system requires only one integrated sensor to switch to electronic support measure (ESM) mode within each tracking cycle to update the angle measurement information of target radiation source, while the other integrated sensors still work in the original planned mode and task. …”
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375
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Cascaded Directional Coupler-Based Triplexer Working on Spectroscopically Relevant Wavelengths for Multiple Gas Detection
Published 2025-02-01“…The triplexer’s functions focus on enhancing the coupling efficiency and selectivity, while facilitating the on-chip integration of diode lasers. …”
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377
Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain
Published 2025-01-01“…Agriculture is essential for living in the Indian Himalayan region (IHR), as it functions as the main occupation and source of income. …”
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378
Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability
Published 2025-05-01“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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379
Energy-Efficiency using Critical Nodes Detection Problem in Industrial Wireless Sensor Networks (IWSNs)
Published 2025-03-01“…Experiments simulation validates our proposed approach, approving its efficiency in reducing significant energy consumption while preserving connectivity and functionality for industrial systems. Furthermore, the results highlight the potential of using critical node analysis to support sustainable and efficient operations in resource-constrained industrial environments. …”
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380