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321
Multi task detection method for operating status of belt conveyor based on DR-YOLOM
Published 2025-06-01“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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322
Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features
Published 2025-03-01“…Seventeen ML algorithms were applied to a dataset of voice recordings from Healthy Control and PD individuals, sourced from a publicly available repository. We leveraged the PyCaret Python library's ML algorithms and functions, which were introduced in this article, to demonstrate their simplicity and effectiveness in dealing with real-world data. …”
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323
A New Modeling Method for Meteorological Information of Regional Distributed Photovoltaic Power Generation Based on Multi‐Source Information Fusion
Published 2025-08-01“…Precise meteorological information is the foundation for achieving these functions. However, DPV sites are typically scattered with small installed capacities and generally lack dedicated weather stations. …”
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Raw-Data Driven Functional Data Analysis with Multi-Adaptive Functional Neural Networks for Ergonomic Risk Classification Using Facial and Bio-Signal Time-Series Data
Published 2025-07-01“…To overcome these challenges, this paper proposes a Multi-Adaptive Functional Neural Network (Multi-AdaFNN), a novel method that integrates functional data analysis with deep learning techniques. …”
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326
AI Chatbots and Cognitive Control: Enhancing Executive Functions Through Chatbot Interactions: A Systematic Review
Published 2025-01-01“…The criteria aligned with the study objectives, ensuring a focus on AI chatbots and the impact of conversational agents on executive function. The initial collection totaled <i>n</i> = 115 articles; however, the eligibility requirements led to the final selection of <i>n</i> = 10 studies. …”
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327
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328
Phage display of cDNA libraries: enrichment of cDNA expression using open reading frame selection
Published 2004-06-01“…The high level of cDNA expression obtained by ORF selection suggests that ORF-enriched phage cDNA libraries prepared by these methods will be useful as functional genomics tools for identifying natural ligands from various source tissues.…”
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329
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330
Research on Underwater Target Detection Technology Based on SMV-YOLOv11n
Published 2025-01-01“…High-precision underwater object detection is a crucial component for improving the efficiency of marine resource development. …”
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331
Walkability Evaluation of Historical and Cultural Districts Based on Multi-Source Data: A Case Study of the Former Russian Concession in Hankou
Published 2025-05-01“…Key issues such as low spatial quality and functional disorder were identified, and targeted optimization strategies are proposed. …”
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332
Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection
Published 2025-07-01“…We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. …”
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333
Object detection with afordable robustness for UAV aerial imagery: model and providing method
Published 2024-08-01“…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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334
3L-YOLO: A Lightweight Low-Light Object Detection Algorithm
Published 2024-12-01“…Existing methods often use image enhancement to improve detection, which results in a large amount of computational resource consumption. …”
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335
Automatic detection of foreign object intrusion along railway tracks based on MACENet.
Published 2025-01-01“…Ensuring high accuracy and efficiency in foreign object intrusion detection along railway lines is critical for guaranteeing railway operational safety under limited resource conditions. …”
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336
Rice disease detection method based on multi-scale dynamic feature fusion
Published 2025-05-01“…These optimizations enable efficient deployment on resource-constrained mobile devices, making the model highly suitable for real-time disease detection in practical agricultural scenarios where hardware limitations are critical. …”
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337
Real time wire rope detection method based on Rockchip RK3588
Published 2025-08-01“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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338
An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet
Published 2025-04-01“…IntroductionIn the aviation field, drone search and rescue is a highly urgent task involving small target detection. In such a resource-constrained scenario, there are challenges of low accuracy and high computational requirements.MethodsThis paper proposes IYFVMNet, an improved lightweight detection network based on YOLOv8. …”
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339
SGSNet: a lightweight deep learning model for strawberry growth stage detection
Published 2024-12-01“…Finally, the Inner-IoU optimization loss function is applied to accelerate model convergence and enhance detection accuracy.ResultsTesting results indicate that SGSNet performs exceptionally well across key metrics, achieving 98.83% precision, 99.45% recall, 99.14% F1 score, 99.50% mAP@0.5, and a loss value of 0.3534. …”
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340