Can Artificial Intelligence Technology Help Achieving Good Governance: A Public Policy Evaluation Method Based on Artificial Neural Network by Zhinan Xu, Zijun Liu, Hang Luo

“…By leveraging empirical data and a deep learning model based on convolutional neural networks (CNN), the model achieves a high accuracy of 93.40%, surpassing most comparable models. …”
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Updated review on diagnosis of Helicobacter pylori by R. Ugiagbe, S. Smith

“…Enhanced endoscopic and histopathological diagnosis also featured Computer Assisted Diagnosis systems and H. pylori deep learning models. Molecular diagnostic techniques include H. pylori reflexive stool testing, whole genomic sequencing as well as PCR diagnostics and clarithromycin resistance testing.…”
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The Daily Container Volumes Prediction of Storage Yard in Port with Long Short-Term Memory Recurrent Neural Network by Yinping Gao, Daofang Chang, Ting Fang, Yiqun Fan

“…The effective forecast of container volumes can provide decision support for port scheduling and operating. In this work, by deep learning the historical dataset, the long short-term memory (LSTM) recurrent neural network (RNN) is used to predict daily volumes of containers which will enter the storage yard. …”
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Single and Multiwavelength Detection of Coronal Dimming and Coronal Wave Using Faster R-CNN by Zongxia Xie, Chunyang Ji

“…Different from the methods used before, we introduce the idea of deep learning. We train single-wavelength and multiwavelength models based on Faster R-CNN. …”
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Dual Domain Swin Transformer based Reconstruction method for Sparse-View Computed Tomography by Jonas Van der Rauwelaert, Caroline Bossuyt, Jan Sijbers

“…Our method comprises three key blocks: sinogram upsampling via linear interpolation, initial reconstruction using deep learning in both domains, and residual refinement. …”
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Self-Correction Ship Tracking and Counting with Variable Time Window Based on YOLOv3 by Chun Liu, Jian Li

“…Combining the target HSV color histogram features and LBP local features’ target, object recognition and selection are realized by using the deep learning model due to its efficiency in extracting object characteristics. …”
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Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance by Angela Cesaro, Samuel C. Hoffman, Payel Das, Cesar de la Fuente-Nunez

“…While conventional tests delay diagnosis, AI-driven methods like machine learning and deep learning assist in pathogen detection, resistance prediction, and drug discovery. …”
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REMAINING USEFUL LIFE OF ROLLING BEARING BASED ON t⁃SNE by ZHONG JianHua, HUANG Cong, ZHONG ShunCong, XIAO ShunGen

“…Due to the limited bearing degradation data under actual working conditions,it is impossible to obtain enough degradation data to train the neural network,it is difficult to obtain good prediction results in the deep learning network,so a new fusion method was proposed.Firstly,the features of the original vibration signal was extracted,dozens of dimensional features were obtained through the ensemble empirical mode decomposition(EEMD)and the singular value decomposition(SVD),and the effective features such as kurtosis and mean value commonly used in remaining useful life prediction were added,then the decision tree to filter out 15⁃dimensional features was used the data was obtained by double exponential model fitting and the degraded signal was reduced to a linear trend through t⁃SNE.The linear degradation trend has better generalization in prediction than the exponential trend,and the prediction accuracy is superior to support veotor regression(SVR)and deep belief network(DBN)model.…”
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Novel image registration algorithm for scene-matching navigation by Hongrui YANG, Qiju ZHU, Peixian CAO, Hao GU, Dongdong ZHAO

“…The results demonstrate that our method considerably improves computational efficiency while maintaining matching precision. Moreover, unlike deep learning algorithms that require extensive data training for generalization, our algorithm achieves the necessary level of generalization without such extensive training. …”
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Perbandingan Prediksi Penggunaan Listrik dengan Menggunakan Metode Long Short Term Memory (LSTM) dan Recurrent Neural Network (RNN) by Nurfatima Selle, Novanto Yudistira, Candra Dewi

“…Our method uses are Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM), which is a deep learning architecture that able to capture time-series data. …”
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ViTAU: Facial paralysis recognition and analysis based on vision transformer and facial action units by Jia GAO, Wenhao CAI, Junli ZHAO, Fuqing DUAN

“…With the rapid advancement of deep learning and computer vision technologies, automatic recognition of facial paralysis has become feasible, offering a more accurate and objective diagnostic approach. …”
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Neural Network and Hybrid Methods in Aircraft Modeling, Identification, and Control Problems by Gaurav Dhiman, Andrew Yu. Tiumentsev, Yury V. Tiumentsev

“…Such a variant opens up the possibility of involving deep learning technology in the construction of motion models for controlled systems. …”
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Framework for smartphone-based grape detection and vineyard management using UAV-trained AI by Sergio Vélez, Mar Ariza-Sentís, Mario Triviño, Antonio Carlos Cob-Parro, Miquel Mila, João Valente

“…Recent technological and machine learning advancements, particularly in deep learning, have provided the tools necessary to create more efficient, automated processes that significantly reduce the time and effort required for these tasks. …”
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Automatic MRI Lymph Node Annotation From CT Labels by Souraja Kundu, Yuji Iwahori, M. K. Bhuyan, Manish Bhatt, Boonserm Kijsirikul, Aili Wang, Akira Ouchi, Yasuhiro Shimizu

“…This study focuses on creating automatic lymph node annotation in MRI images using available CT annotations via deep-learning models. Training such models typically requires partial MRI labels for semi-supervision. …”
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Enhancing safety with an AI-empowered assessment and monitoring system for BSL-3 facilities by Yi-Ling Fan, Ching-Han Hsu, Ju-Yu Wu, Ying-Ying Tsai, Wei J. Chen, Min-Shi Lee, Fang-Rong Hsu, Lun-De Liao

“…The internal laboratory management system used a deep learning model to delineate alert zones and monitor compliance with the imposed safety protocols. …”
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Perbandingan Arsitektur Convolutional Neural Network Pada Klasifikasi Pneumonia, COVID-19, Lung Opacity, dan Normal Menggunakan Citra Sinar-X Thoraks by Agung Wahyu Setiawan

“…Several studies have been conducted using a deep learning approach based on Convolutional Neural Networks (CNN) architecture. …”
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AiGPro: a multi-tasks model for profiling of GPCRs for agonist and antagonist by Rahul Brahma, Sunghyun Moon, Jae-Min Shin, Kwang-Hwi Cho

“…Scientific Contribution We introduce a deep learning-based multi-task model to generalize the agonist and antagonist bioactivity prediction for GPCRs accurately. …”
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Pengukuran Performa Apache Spark dengan Library H2O Menggunakan Benchmark Hibench Berbasis Cloud Computing by Aminudin Aminudin, Eko Budi Cahyono

“…Data tersebut diproses menggunakan salah satu model machine learning yaitu deep learning dengan membagi beberapa node yang telah terbentuk di lingkungan cloud computing dengan memanfaatkan library H2O. …”
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Leveraging public AI tools to explore systems biology resources in mathematical modeling by Meera Kannan, Gabrielle Bridgewater, Ming Zhang, Michael L. Blinov

“…Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.…”
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AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations by Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta, Rupert A. C. Croft, Tiziana Di Matteo, Yueying Ni, Simeon Bird, Yin Li

“…Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly enhance low-resolution (LR) runs with statistically correct fine details. …”
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