Target Detection and Robotic Arm Grasp Pose Estimation Based on YOLOv5 and Transfer Learning by Li Wanyan, Ruan Guanqiang, Zhang Zhendong

“…For traditional machine learning algorithms, visual recognition algorithms have low recognition accuracy and slow running time. …”
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Comparative Analysis of Federated and Centralized Learning Systems in Predicting Cellular Downlink Throughput Using CNN by Kukuh Nugroho, Hendrawan, Iskandar

“…This study utilized Federated Learning (FL) as a machine learning paradigm and employed CNN as a model to predict throughput in the cellular network. …”
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A Surrogate Model for Studying Solar Energetic Particle Transport and the Seed Population by Atilim Guneş Baydin, Bala Poduval, Nathan A. Schwadron

“…In this scenario, adopting a machine learning approach to SEP modeling and prediction is desirable. …”
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STUDY OF DOMAIN ADAPTIVE NETWORK AND BALANCED DYNAMIC DISTRIBUTION ADAPTIVE FAULT MIGRATION DIAGNOSIS OF BEARING UNDER VARIABLE CONDITIONS (MT) by WANG TingXuan, WANG GuiYong, LIU Tao, WANG ZhenYa

“…The complex and changeable working conditions of mechanical equipment in industrial field lead to uneven distribution of fault samples, which brings great trouble to traditional machine learning. In order to solve this problem, proposes a bearing fault transfer diagnosis method based on domain adaptive neural network and balanced dynamic distribution adaptive. …”
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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

“…The random forest model belonging to the machine learning algorithm has many advantages such as strong generalization ability and fast training speed, and it has a strong mapping capability for nonlinear features. …”
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Global Impact Assessment of Internal Climate Variability on Maize Yield Under Climate Change by Guoyong Leng

“…By combining initial condition large ensembles from multiple climate models with machine‐learning based crop model emulators, an ensemble of 2002 global maize yield simulations are conducted. …”
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Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews by Muhammad Afzaal, Muhammad Usman, A. C. M. Fong, Simon Fong, Yan Zhuang

“…Such sentences make the data noisy and degrade the classification accuracy of the machine learning algorithms. This paper presents a fuzzy aspect based opinion classification system which efficiently extracts aspects from user opinions and perform near to accurate classification. …”
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Des-q: a quantum algorithm to provably speedup retraining of decision trees by Niraj Kumar, Romina Yalovetzky, Changhao Li, Pierre Minssen, Marco Pistoia

“…Decision trees are widely adopted machine learning models due to their simplicity and explainability. …”
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Composite Bayesian Optimization in function spaces using NEON—Neural Epistemic Operator Networks by Leonardo Ferreira Guilhoto, Paris Perdikaris

“…Abstract Operator learning is a rising field of scientific computing where inputs or outputs of a machine learning model are functions defined in infinite-dimensional spaces. …”
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Prediction of hemolytic peptides and their hemolytic concentration by Anand Singh Rathore, Nishant Kumar, Shubham Choudhury, Naman Kumar Mehta, Gajendra P. S. Raghava

“…Among classification models, including machine learning (ML), quantum ML, and protein language models, a hybrid model combining random forest (RF) and a motif-based approach achieves the highest area under the receiver operating characteristic curve (AUROC) of 0.921. …”
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Applications of artificial neural networks in health care organizational decision-making: A scoping review. by Nida Shahid, Tim Rappon, Whitney Berta

“…Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduced cost. …”
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Accelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions by Mohammad Madani, Valentina Lacivita, Yongwoo Shin, Anna Tarakanova

“…Abstract Machine learning has advanced the rapid prediction of inorganic materials properties, yet data scarcity for specific properties and capturing thermodynamic stability remains challenging. …”
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Artificial neural networks for stability analysis and simulation of delayed rabies spread models by Ramsha Shafqat, Ateq Alsaadi

“…This approach aimed to expand our understanding of rabies transmission, illustrating the potential of advanced mathematical tools and machine learning in epidemiological modeling.…”
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Application of IoT and Cloud Computing in Automation of Agriculture Irrigation by Khongdet Phasinam, Thanwamas Kassanuk, Priyanka P. Shinde, Chetan M. Thakar, Dilip Kumar Sharma, Md. Khaja Mohiddin, Abdul Wahab Rahmani

“…This system is designed to measure soil moisture and humidity and then process this data in the cloud using a variety of machine learning techniques. Farmers are given the correct information about water content rules. …”
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Integrins identified as potential prognostic markers in osteosarcoma through multi-omics and multi-dataset analysis by Lei Cui, Shuai Zhao, Hai long Teng, Biao Yang, Qian Liu, An Qin

“…This study utilized 209,268 osteosarcoma cells from the GEO database to identify integrin-associated genes using advanced analysis methods. A novel machine learning framework combining 10 algorithms was developed to construct an Integrin-related Signature (IRS), which demonstrated robust predictive power across multiple datasets. …”
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Evolving techniques in sentiment analysis: a comprehensive review by Mahander Kumar, Lal Khan, Hsien-Tsung Chang

“…It explores a spectrum of methodologies, from classical word embedding techniques and machine learning algorithms to recent contextual embedding and advanced transformer models like Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), and T5. …”
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The intersection of digital health and artificial intelligence: Clearing the cloud of uncertainty by Pooyeh Graili, Bijan Farhoudi

“…In the context of numerical data, machine learning algorithms enable prediction, classification, and clustering. …”
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The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest by Xiwen Qin, Dingxin Xu, Xiaogang Dong, Xueteng Cui, Siqi Zhang

“…In order to verify the effectiveness of the proposed method, a comparison is made with the traditional machine learning method. The results suggest that the proposed method can identify different types of faults more accurately and robustly. …”
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Recommended System Optimization in Social Networks Based on Cooperative Filter with Deep MVR Algorithm by Kim Hung Pho

“…In this research, we tried to provide a system of recommendations for introducing new users to previous users and vice versa based on the principles of machine learning. The proposed method is that the data is entered into the program and then the keywords are extracted from them. …”
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Incisor Malocclusion Using Cut-out Method and Convolutional Neural Network by Muhamad Farhin Harun, Azurah A Samah, Muhammmad Imran Ahmad Shabuli, Hairudin Abdul Majid, Haslina Hashim, Nor Azman Ismail, Syiral Mastura Abdullah, Aspalilah Alias

“…In addition, unstructured images with varying sizes and the problem of a machine learning algorithm that does not focus on the region of interest (ROI) for incisor features bring challenges in delivering the treatment. …”
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