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421
DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection
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422
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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423
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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424
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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425
FCMI-YOLO: An efficient deep learning-based algorithm for real-time fire detection on edge devices.
Published 2025-01-01“…The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …”
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426
Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections
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427
SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI
Published 2024-12-01“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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428
Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation
Published 2025-08-01“…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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429
Finite mixtures of functional graphical models: Uncovering heterogeneous dependencies in high-dimensional data.
Published 2025-01-01“…In this work, we propose finite mixtures of functional graphical models (MFGM), which detect the heterogeneous subgroups of the population and estimate single graph for each subgroup by considering the correlation structures. …”
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430
Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium
Published 2025-07-01“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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431
STar-DETR: A Lightweight Real-Time Detection Transformer for Space Targets in Optical Sensor Systems
Published 2025-02-01“…Optical sensor systems are essential for space target detection. However, previous studies have prioritized detection accuracy over model efficiency, limiting their deployment on resource-constrained sensors. …”
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432
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433
Research on a Target Detection Algorithm for Common Pests Based on an Improved YOLOv7-Tiny Model
Published 2024-12-01“…In agriculture and forestry, pest detection is critical for increasing crop yields and reducing economic losses. …”
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434
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435
YOLOv8-CBSE: An Enhanced Computer Vision Model for Detecting the Maturity of Chili Pepper in the Natural Environment
Published 2025-02-01“…Additionally, SRFD and DRFD modules are introduced to replace the original convolutional layers, effectively capturing features at different scales and enhancing the diversity and adaptability of the model through the feature fusion mechanism. To further improve detection accuracy, the EIoU loss function is used instead of the CIoU loss function to provide more comprehensive loss information. …”
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436
Detection of VOCs and Biogenic Amines Through Luminescent Zn–Salen Complex-Tethered Pyrenyl Arms
Published 2024-12-01“…Biogenic amines, resulting from the natural decarboxylation of amino acids, are released into the environment from both natural and industrial sources. Several methods have been developed so far to detect amines in the environment. …”
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437
Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies
Published 2025-01-01“…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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438
Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection
Published 2025-01-01“…It employs an enhanced genetic algorithm (GA) with a unique fitness function, dynamic crossover, and adaptive mutation strategies to achieve model compression, maintain accuracy, and balance exploration and exploitation during evolution. …”
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439
Detection of structural variants linked to mutton flavor and odor in two closely related black goat breeds
Published 2024-10-01Get full text
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440
PdYOLO: A Lightweight Algorithm for Detecting Peach Fruits Against a Peach Tree Background
Published 2024-01-01“…First, the CIOU regression loss function in YOLOv8s is replaced with the WIoUv2 regression loss function, effectively alleviating the negative impact of uneven distribution of positive and negative samples during model training through a more balanced gradient gain distribution strategy, which significantly improves detection accuracy. …”
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