Metric learning unveiling disparities: A novel approach to recognize false trigger images in wildlife monitoring by Rui Zhu, Enting Zhao, Chunhe Hu, Jiangjian Xie, Junguo Zhang, Huijian Hu

“…This study proposes a metric learning-based method for false-triggered image recognition. …”
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Leveraging Deep Learning and Multimodal Large Language Models for Near-Miss Detection Using Crowdsourced Videos by Shadi Jaradat, Mohammed Elhenawy, Huthaifa I. Ashqar, Alexander Paz, Richi Nayak

“…The zero-shot learning method performed better, achieving an accuracy of 81.2% and an F1-score of 81.9%. …”
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Data-Enabled Intelligence in Complex Industrial Systems Cross-Model Transformer Method for Medical Image Synthesis by Zebin Hu, Hao Liu, Zhendong Li, Zekuan Yu

“…More specifically, the proposed method captures locality feature via local discriminator based on CNN and utilizes long-range dependencies to learning global feature through global discriminator based on transformer architecture. …”
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Evaluation of iLead, a generic implementation leadership intervention: mixed-method preintervention–postintervention design by Anne Richter, Caroline Lornudd, Ulrica von Thiele Schwarz, Robert Lundmark, Rebecca Mosson, Ulrika Eskner Skoger, Tatja Hirvikoski, Henna Hasson

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من ناحية المادة الدراسيةـ MTsS Darul Ulum Banda Aceh تدريس النحو بـــــ by Cut Nadia Salsabila, Salami Mahmud, Fajriah Fajriah

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Lessons Learned From Co-Designing Educational Programs for Student and Practicing Healthcare Professionals in Nursing Homes: A Participatory Qualitative Study by Irene J.M. Muller-Schoof, Marjolein E. A. Verbiest, Miranda Snoeren, Katrien G. Luijkx

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Real-Time Posture Correction of Squat Exercise: A Deep Learning Approach for Performance Analysis and Error Correction by Prashant Rao, C. S. Asha, P. Raghavendra Rao

“…A deep learning-based regressor, trained on a dataset of squat videos, estimates the correct joint angles. …”
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Research on Spam Filters Based on NB Algorithm by Su Shengyue

“…As spam becomes more complex, traditional rule-based methods struggle to meet the needs of modern email systems. …”
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Multi-scale sparse convolution and point convolution adaptive fusion point cloud semantic segmentation method by Yuxuan Bi, Peng Liu, Tianyi Zhang, Jialin Shi, Caixia Wang

“…By prioritizing the importance of input feature positions, this module enhances the sparse learning performance of critical feature information. …”
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Research Progress and Technology Outlook of Deep Learning in Seepage Field Prediction During Oil and Gas Field Development by Tong Wu, Qingjie Liu, Yueyue Wang, Ying Xu, Jiale Shi, Yu Yao, Qiang Chen, Jianxun Liang, Shu Tang

“…Key processes based on Deep Learning, such as feature engineering, network structure design, and physical constraint integration mechanisms, are further explored. …”
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The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity by James E. Galvin, Michael J. Kleiman, Heather M. Harris, Paul W. Estes

“…The CARM differentiated between individuals with amyloid and without amyloid by PET (p < 0.001, Cohen’s d = 0.618) and blood-based biomarkers (p’s < 0.001). Amyloid positivity and cognitive impairment increased across four CARM thresholds (p < 0.001). …”
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Automated Detection, Localization, and Severity Assessment of Proximal Dental Caries from Bitewing Radiographs Using Deep Learning by Mashail Alsolamy, Farrukh Nadeem, Amr Ahmed Azhari, Walaa Magdy Ahmed

“…This paper presents a deep-learning-based system to improve the evaluation process by detecting proximal dental caries from BRs and classifying their severity in accordance with ICCMS^TM guidelines. …”
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Coordinated Reentry Guidance with A* and Deep Reinforcement Learning for Hypersonic Morphing Vehicles Under Multiple No-Fly Zones by Cunyu Bao, Xingchen Li, Weile Xu, Guojian Tang, Wen Yao

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Image-based and textbook-based virtual reality training on operational skills among junior residents: a proof of concept study by Wan-Ni Lin, Hai-Hua Chuang, Yi-Ping Chao, Li-Jen Hsin, Chung-Jan Kang, Tuan-Jen Fang, Hsueh-Yu Li, Li-Ang Lee

“…However, the impact of IBVR on learning outcomes requires further investigation. This study aims to assess the efficacy of IBVR compared to textbook-based VR (TBVR) in teaching operational skills to junior residents. …”
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Scene Target 3D Point Cloud Reconstruction Technology Combining Monocular Focus Stack and Deep Learning by Yanzhu Hu, Yingjian Wang, Song Wang

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Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

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Error Compensation for Dead Reckoning Based on SVM by Xin LI, Xiaoming WANG, Jianguo WU, Jiwei ZHAO, Jiacheng XIN, Kai CHEN, Bin ZHANG

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Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning by Jakub Horvath, Pavel Jedlicka, Marie Kratka, Zdenek Kubat, Eduard Kejnovsky, Matej Lexa

“…Results We used machine learning methods suitable for DNA sequence classification and applied them to a large dataset of plant LTR retrotransposon sequences. …”
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DSGRec: dual-path selection graph for multimodal recommendation by Zihao Liu, Wen Qu

“…Although methods based on graph convolutional networks (GCNs) have achieved notable success, they still face two key limitations: (1) the narrow interpretation of interaction information, leading to incomplete modeling of user behavior, and (2) a lack of fine-grained collaboration between user behavior and multi-modal information. …”
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Insights into nurse educators' use of ChatGPT in active teaching methods: A cross-sectional pilot study by Asma Bouriami, Kamal Takhdat, Sana Barkatou, Hajar Chiki, Samia Boussaa, Ahmed Rhassane El Adib

“…Furthermore, male educators are five times more likely to believe that ChatGPT facilitates students cheating (OR = 5.147 (1.641; 16.141)).Despite being aware of the challenges associated with ChatGPT, educators in our sample demonstrate limited awareness of its potential applications in active teaching methods. For instance, only 33.33% use ChatGPT in problem-based learning, while a mere 10% use ChatGPT in simulation-based learning. …”
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