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281
Efficient Packaging Line Object Counting by Cross-Frame Association With Wavelet Convolutions and Trajectory Compensation
Published 2025-01-01“…WT-YOLO significantly improves detection accuracy in complex scenes with occlusions and irregular shapes by expanding the receptive field of the network and capturing low-level shape signals, thereby enhancing the network’s shape bias. …”
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282
PdYOLO: A Lightweight Algorithm for Detecting Peach Fruits Against a Peach Tree Background
Published 2024-01-01“…Finally, a new head layer P2-SLD was designed, which replaced the original detection head with a shared lightweight detection head SLD, introduced the P2 layer and removed the P5 layer, which improved the lightweight level of the model, improved the processing efficiency and reduced the energy consumption while ensuring the detection accuracy. …”
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283
Streamlining Deep Learning Network for Real-time Sea Turtle Detection
Published 2024-09-01“…A new turtle dataset is proposed that contains lighting, blur, occlusion, and complex background challenges. The evaluation results show that the proposed model performs higher accuracy than other lightweight object detection models. …”
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284
A Dynamic Evaluation Method for Collaborative Search Efficiency of Multi-Sonar Systems Under Uncertain Situations
Published 2025-05-01“…It discretizes the sonar search path and target motion trajectory in the time and space, and calculates the sonar detection efficiency point by point, which can overcome the challenge of uncertain situation conditions due to the uncertainty of target motion by dynamic spatial-temporal deduction. …”
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285
VBP-YOLO-prune: Robust apple detection under variable weather via feature-adaptive fusion and efficient YOLO pruning
Published 2025-09-01“…These results demonstrate that VBP-YOLO-prune provides a practical and efficient solution for real-time fruit detection in complex environments. …”
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286
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288
SAM-Based Efficient Feature Integration Network for Remote Sensing Change Detection: A Case Study on Macao Sea Reclamation
Published 2025-01-01“…To utilize the visual recognition capabilities of SAM for improving RSCD, we propose an SAM-based efficient feature integration network (EFI-SAM). Random fourier features adaptor (RFFA) is utilized to enhance Mobile SAM’s capability for extracting general features from complex RSIs, resulting in adaptive Mobile SAM, which serves as the feature extractor of EFI-SAM. …”
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289
Assessment of Doppler Wind Lidar Detection Efficiency and Influencing Factors at Plateau Airport: A Case Study of Lhasa Gonggar Airport
Published 2024-12-01“…Doppler wind lidar (DWL) demonstrates significant advantages in wind field detection under clear weather conditions and has been widely applied in airports with complex wind environments. …”
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290
HGCS-Det: A Deep Learning-Based Solution for Localizing and Recognizing Household Garbage in Complex Scenarios
Published 2025-06-01“…However, due to the interference of complex environments, coupled with the influence of the irregular features of garbage, garbage detection in complex scenarios still faces significant challenges. …”
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291
Enhancing wind turbine blade damage detection with YOLO-Wind
Published 2025-05-01“…Furthermore, a newly added P2 detection layer enhances multi-scale defect recognition in complex environments. …”
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292
UV–Vis Detection of Thioacetamide: Balancing the Performances of a Mn(III)-Porphyrin, Gold Colloid, and Their Complex for Selecting the Most Sensitive Material
Published 2025-05-01“…It could be concluded that Mn-3,4-diMeOPP could detect/quantify thioacetamide (TAA) in the range 3.13 × 10<sup>−8</sup> M–7.67 × 10<sup>−7</sup> M in a linear fashion, with a 99.85% confidence coefficient. …”
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293
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294
RDRM-YOLO: A High-Accuracy and Lightweight Rice Disease Detection Model for Complex Field Environments Based on Improved YOLOv5
Published 2025-02-01“…Rice leaf diseases critically threaten global rice production by reducing crop yield and quality. Efficient disease detection in complex field environments remains a persistent challenge for sustainable agriculture. …”
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295
Para-YOLO: An Efficient High-Parameter Low-Computation Algorithm Based on YOLO11n for Remote Sensing Object Detection
Published 2025-01-01“…Moreover, the increasing demand for real-time onboard image processing imposes stringent requirements on both algorithmic complexity and detection accuracy. To overcome these challenges, we propose Para-YOLO, an efficient and cost-effective algorithm consisting of a novel feature fusion network and three innovative modules. …”
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296
Optimizing Security in IoT Ecosystems Using Hybrid Artificial Intelligence and Blockchain Models: A Scalable and Efficient Approach for Threat Detection
Published 2025-01-01“…Traditional security solutions, based on centralized architectures, are neither scalable nor efficient enough to handle the increasing complexity and number of IoT devices, leading to high latencies, increased energy consumption, and inadequate intrusion detection. …”
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297
THE EFFICIENCY OF TECHNIQUE OF DOUBLE ARCHES BY THE TREATMENT OF PATIENTS WITH ANOMALIES OF OCCLUSION
Published 2022-10-01“…As a result of examination and treatment of patients of the first period of mature age with various forms of occlusion anomalies it was detected an efficiency of preformed arches treatment and technique of double arches taking into account individual parameters of the dental arches on the morphometric parameters of the craniofacial complex in conjunction with the main parameters of dentoalveolar arches and individual tooth sizes. …”
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298
Assessing the Role of EEG Biosignal Preprocessing to Enhance Multiscale Fuzzy Entropy in Alzheimer’s Disease Detection
Published 2025-06-01“…Quantitative electroencephalography (QEEG) has emerged as a promising tool for detecting Alzheimer’s disease (AD). Among QEEG measures, Multiscale Fuzzy Entropy (MFE) shows great potential in identifying AD-related changes in EEG complexity. …”
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299
Signal Detection for Enhanced Spatial Modulation-Based Communication: A Block Deep Neural Network Approach
Published 2025-02-01“…In ESM, traditional signal detection methods such as maximum likelihood (ML) have the drawback of high complexity. …”
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300
NavBLIP: a visual-language model for enhancing unmanned aerial vehicles navigation and object detection
Published 2025-01-01“…Additionally, these methods often fail to effectively integrate multimodal inputs, which restricts their adaptability and generalization capabilities when facing complex and diverse scenarios.MethodsTo address these challenges, we introduce NavBLIP, a novel visual-language model specifically designed to enhance UAV navigation and object detection by utilizing multimodal data. …”
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