Defect Detection Method for Large-Curvature and Highly Reflective Surfaces Based on Polarization Imaging and Improved YOLOv11 by Zeyu Yu, Dongyun Wang, Hanyang Wu

“…These enhancements significantly improve the model’s generalization capability across different defect types. Experimental results show that, compared to state-of-the-art object detection models, the proposed model achieves a 3.9% increase in precision over the best-performing baseline, along with notable improvements in recall, mAP50, and other key performance indicators.…”
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PNSS: An online plant name service system by Qiu Jinshui, Zhang Jianwen, Jin Tao, Zhuang Huifu

“…However, these resources are scattered across various database websites or personal computers. …”
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Unbiased machine learning-assisted approach for conditional discretization of human performances by Thepparit Banditwattanawong, Masawee Masdisornchote

“…Performance discretization maps numerical performance values to ordinal categories or performance ranking labels. …”
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Consensus artificial intelligence-driven prognostic signature for predicting the prognosis of hepatocellular carcinoma: a multi-center and large-scale study by Wen Wen, Rui Wang

“…This study developed a consensus artificial intelligence-derived prognostic signature (CAIPS) by integrating ten machine learning algorithms (101 methods) across six multi-center HCC cohorts (n = 1110). …”
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Research on the Method of Artificial Intelligence for Identifying Urban Land-Use Types Based on Areas of Interest (AOI) and Multi-Source Data by Miaoyi Li, Ningrui Zhu

“…Departing from existing data weighting algorithms, this research applies artificial intelligence techniques, utilizing the categorical information of AOI data as labels. …”
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Tri-band vehicle and vessel dataset for artificial intelligence research by Yingjian Liu, Gangnian Zhao, Shuzhen Fan, Cheng Fei, Junliang Liu, Zhishuo Zhang, Liqian Wang, Yongfu Li, Xian Zhao, Zhaojun Liu

“…About 60% of the dataset has been manually labeled with object instances to train and evaluate well-established object detection algorithms. After training with YOLOv8 and SSD object detection algorithms, all models have mAP values above 0.6 at an IoU threshold of 0.5, which indicates good recognition performance for this dataset. …”
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SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM) by Xiang Cheng, Ziwei Huang, Yong Yu, Lu Bai, Mingran Sun, Zengrui Han, Ruide Zhang, Sijiang Li

“…The SynthSoM dataset is open-sourced and provides consistent data for cross-comparing SoM-related algorithms.…”
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PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

“…Experiments on the enhanced Peking University PCB defect dataset show that PCES-YOLO achieves a mAP50 of 97.3% and a mAP50–95 of 77.2%. Compared to YOLOv11n, it shows improvements of 3.6% in mAP50 and 15.2% in mAP50–95. …”
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Robust zero-watermarking for color images using hybrid deep learning models and encryption by Hager A. Gharib, Noha M. M. Abdelnapi, Khalid M. Hosny

“…Compared to existing zero-watermarking algorithms, the proposed method shows superior robustness and security, making it highly effective for multimedia copyright protection.…”
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An Ensemble Learning Approach for Drought Analysis and Forecasting in Central Bangladesh by Md. Alomgir Hossain, Momotaz Begum, Md. Nasim Akhtar, Md. Alamin Talukder, Nomanur Rahman, Mahfuzur Rahman

“…SPI and SPEI were mapped within a GIS environment to assess drought hazards and identify key social and physical vulnerability factors. …”
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A novel dataset and deep learning object detection benchmark for grapevine pest surveillance by Giorgio Checola, Paolo Sonego, Roberto Zorer, Valerio Mazzoni, Franca Ghidoni, Alberto Gelmetti, Pietro Franceschi

“…The results, evaluated through 10-fold cross validation, revealed promising detection accuracy, with YOLOv8 achieving an mAP@0.5 of 92%, and an F1-score above 90%, with an mAP@[0.5:0.95] of 66%. …”
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On Introduction to q1,q2-Linear Diophantine Fuzzy Sets and Their Applications by Muhammad Bilal Khan, Adrian Marius Deaconu, Javad Tayyebi, Bandar Bin-Mohsin, Loredana Ciurdariu, Miguel Vivas Cortez, Nurnadiah Zamri

“…The notion of parameter mappings is about creating and managing a structured relationship between parameters across different systems or processes. …”
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Identification of Vehicle Logos in Deep Learning: A Comprehensive Survey by Mustafa Noaman Kadhim, Ammar Hussein Mutlag, Dalal Abdulmohsin Hammood, Nurulisma Binti Hj. Ismail

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Identifying Influential Nodes in Complex Networks via Transformer with Multi-Scale Feature Fusion by Tingshuai Jiang, Yirun Ruan, Tianyuan Yu, Liang Bai, Yifei Yuan

“…Experimental analysis confirms that MSF-Former achieves consistently high accuracy in the identification of influential nodes across real-world and synthetic networks.…”
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Integrated Single-Cell and Spatial Transcriptomic Analysis Identifies ISR-Related Genes Driving Immune Regulation in Parkinson’s Disease by Jiang H, Zhang X, Feng S, Feng W

“…ISR scores were compared across brain cell types, and differentially expressed genes in microglia were further screened using Lasso regression and random forest algorithms. …”
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Temperature prediction for forging a large S355NL steel flange for offshore wind turbines using neural network and numerical simulation by Yu Chen, Jinfu Zhao, Ling Kong, Jianjun Zhang, Zhixin Huang, Dayong Li, Yuhui Wang

“…Finite element numerical simulations subsequently mapped the temperature field of large ring forgings across different forging scenarios at varying die speeds. …”
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MTGNet: Multi-Agent End-to-End Motion Trajectory Prediction with Multimodal Panoramic Dynamic Graph by Yinfei Dai, Yuantong Zhang, Xiuzhen Zhou, Qi Wang, Xiao Song, Shaoqiang Wang

“…With the rapid development of autonomous driving technology, multi-agent trajectory prediction has become the core foundation of autonomous driving algorithms. Efficiently and accurately predicting the future trajectories of multiple agents is key to evaluating the reliability and safety of autonomous driving vehicles. …”
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Efficient guided inpainting of larger hole missing images based on hierarchical decoding network by Xiucheng Dong, Yaling Ju, Dangcheng Zhang, Bing Hou, Jinqing He

“…Abstract When dealing with images containing large hole-missing regions, deep learning-based image inpainting algorithms often face challenges such as local structural distortions and blurriness. …”
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Application of Machine Learning and Multi-Dimensional Perception in Urban Spatial Quality Evaluation: A Case Study of Shanghai Underground Pedestrian Street by Tianning Yao, Yao Xu, Liang Sun, Pan Liao, Jin Wang

“…The study proposes a comprehensive and applicable spatial quality evaluation model integrating spatial quantification methods, machine learning algorithms, and multidimensional perception measurements. …”
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Artificial intelligence in the diagnosis and management of dysphagia: a scoping review by Rayane Délcia da Silva, Suzanne Bettega Almeida, Flávio Magno Gonçalves, Bianca Simone Zeigelboim, José Stechman-Neto, Angela Graciela Deliga Schroder, Weslania Viviane Nascimento, Rosane Sampaio Santos, Cristiano Miranda de Araujo

“…Regarding the underlying diseases present in the patients who participated in the studies, there was a predominance of various neurological conditions. The algorithms used varied across the categories of Machine Learning, Deep Learning, and Computer Vision, with a predominance in the use of Deep Learning. …”
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