Race to the Moon or the Bottom? Applications, Performance, and Ethical Considerations of Artificial Intelligence in Prosthodontics and Implant Dentistry by Amal Alfaraj, Toshiki Nagai, Hawra AlQallaf, Wei-Shao Lin

Subjects: “…deep learning…”
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LSTM+MA: A Time-Series Model for Predicting Pavement IRI by Tianjie Zhang, Alex Smith, Huachun Zhai, Yang Lu

Subjects: “…deep learning…”
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Research on Concrete Beam Damage Detection Using Convolutional Neural Networks and Vibrations from ABAQUS Models and Computer Vision by Xin Bai, Zi Zhang

Subjects: “…deep learning…”
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Multi-Tier Blockchain-Based Land Registry Using Fog Computing by Ashank Priyadarshi, Thankaraja Raja Sree

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Multi-Condition Remaining Useful Life Prediction Based on Mixture of Encoders by Yang Liu, Bihe Xu, Yangli-ao Geng

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The Role of Artificial Intelligence (AI) in Transforming Small and Medium Enterprises (SMEs): by Mugisha, Justin, Francis Adyanga, Akena, Ocan, Johnson

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Uso de deep learning para a construção de um modelo de recuperação da informação aplicado para o setor de mineração no Brasil by Luander Cipriano de Jesus Falcão, Brenner Lopes, Renato Rocha Souza, Ricardo Rodrigues Barbosa

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Predicting the heat capacity of strontium-praseodymium oxysilicate SrPr4(SiO4)3O using machine learning, deep learning, and hybrid models by Amir Hossein Sheikhshoaei, Ali Khoshsima, Davood Zabihzadeh

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Corrigendum to “Constraint-incorporated deep learning model for predicting heat transfer in porous media under diverse external heat fluxes” [Energy and AI 18 (2024) 100425] by Ziling Guo, Hui Wang, Huangyi Zhu, Zhiguo Qu

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A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study. by Ilaria Amodeo, Giorgio De Nunzio, Genny Raffaeli, Irene Borzani, Alice Griggio, Luana Conte, Francesco Macchini, Valentina Condò, Nicola Persico, Isabella Fabietti, Stefano Ghirardello, Maria Pierro, Benedetta Tafuri, Giuseppe Como, Donato Cascio, Mariarosa Colnaghi, Fabio Mosca, Giacomo Cavallaro

“…We propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH to develop forecasting models in prenatal epoch, based on the integrated analysis of clinical data, to provide neonatal PH as the first outcome and, possibly: favorable response to fetal endoscopic tracheal occlusion (FETO), need for Extracorporeal Membrane Oxygenation (ECMO), survival to ECMO, and death. …”
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Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels by Fan Xu, Xin Shu, Xin Li, Xiaodi Zhang

“…In this paper, we use the stacked denoising autoencoder (SDAE) model in deep learning to construct HI directly from the microgrid power equipment of raw signals in bearings. …”
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Classification of Invoice Images By Using Convolutional Neural Networks by Sait Ali Uymaz, Ömer Arslan

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RESEARCH ON TRAFFIC CONGESTION DETECTION FROM CAMERA IMAGES IN A LOCATION OF DA LAT by Nguyen Thi Luong

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Object Detection by Neural Network for Smart Home by Ibrahim Mekawy

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A Method for Measuring Strawberry Leaf Area Based on Three-Dimensional Point Cloud Instance Segmentation by Zhipeng Li, Shusheng Wang, Yuanping Su, Dongyun Yu

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Non-Rigid Cycle Consistent Bidirectional Network with Transformer for Unsupervised Deformable Functional Magnetic Resonance Imaging Registration by Yingying Wang, Yu Feng, Weiming Zeng

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Computer Vision-Based Framework for Data Extraction From Heterogeneous Financial Tables: A Comprehensive Approach to Unlocking Financial Insights by Iftakhar Ali Khandokar, Priya Deshpande

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Real-Time Classification of Deep and Non-Deep Sleep With Comparative Intervention Experiments by Mo Xia, Hongxi Xue, Boning Li, Jianting Cao

Subjects: “…Deep learning…”
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A novel machine learning approach for portfolio optimization by Saman Haratizadeh, Fatemeh Rezaee

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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

Subjects: “…Deep learning…”
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