Real-Time Reinforcement Learning for Optimal Viewpoint Selection in Monocular 3D Human Pose Estimation by Sanghyeon Lee, Yoonho Hwang, Jong Taek Lee

“…To address these challenges, we propose a real-time reinforcement learning-based viewpoint selection method that dynamically adjusts the camera viewpoint to optimize pose estimation. Our method extracts features encoding depth ambiguity and uncertainty from 2D-to-3D lifting, allowing the model to identify the optimal camera movements without requiring multiple cameras. …”
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Genes adopt non‐optimal codon usage to generate cell cycle‐dependent oscillations in protein levels by Milana Frenkel‐Morgenstern, Tamar Danon, Thomas Christian, Takao Igarashi, Lydia Cohen, Ya‐Ming Hou, Lars Juhl Jensen

“…Moreover, genes encoding proteins that cycle at the protein level exhibit non‐optimal codon preferences. …”
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Multi scale supervised entropy weighted binary pattern for texture classification by Xiaochun Xu, Bin Li

“…Secondly, to select the optimal texture scale from the Gaussian scale space, the paper proposes a local entropy-based optimal selection mechanism (LEOSM) grounded in the uniform properties of the proposed local entropy-weighted histogram. …”
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Research on tugboat scheduling optimization model considering the reliability of tugboat matching scheme by Yangjun Ren, Mengchi Li, Yushun Lei, Yan Zhou, Di Liu, Jianjun Tu, Botang Li

“…The results verify the feasibility of the proposed priority-based encoding Memetic algorithm. The enhanced multi-attribute group decision-making method helps decision-makers quickly select suitable matching schemes and optimize tugboat scheduling, demonstrating effective reliability evaluation and planning optimization.…”
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Comparative analysis of Diospyros (Ebenaceae) plastomes: Insights into genomic features, mutational hotspots, and adaptive evolution by Yue Huang, Qing Ma, Jing Sun, Li‐Na Zhou, Chan‐Juan Lai, Pan Li, Xin‐Jie Jin, Yong‐Hua Zhang

“…The present study performed comparative genomic and evolutionary analyses on plastomes of 45 accepted Diospyros species, including three newly sequenced ones. …”
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Optimization of Village Grouping Using Comparison of K-Means and K-Medoids Methods by Eza Rahmanita, Yeni Kustiyahningsih, Putri Nihayatul Husna, Adhelia Firdaus Al-Najib

“…Data Pre-processing steps include data transformation, label encoding, imputation, and Min-Max normalization. Cluster optimization was performed using the Sum of Squared Errors (SSE) method. …”
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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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Improvement of reading platforms assisted by the spring framework: A recommendation technique integrating the KGMRA algorithm and BERT model by Yawen Su

“…It not only offers significant application value but also contributes new perspectives for the optimization and innovation of future recommendation systems.…”
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Enhancing Data Recovery in RAID6: A Comparative Analysis of Row-Diagonal Parity Codes by Zhang Wenxu

“…Comparative analysis highlights the computational advantages of RDP codes over traditional methods such as Reed-Solomon and EVENODD Codes. …”
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A comparative study of machine learning models for automated detection and classification of retinal diseases in Ghana. by Gifty Duah, Eric Nyarko, Anani Lotsi

“…The preprocessing techniques employed included data augmentation, resizing, and one-hot encoding. We also used the Gaussian Process-based Bayesian Optimization (GPBBO) approach to fine-tune the hyperparameters. …”
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A Fluid Flow‐Based Deep Learning (FFDL) Architecture for Subsurface Flow Systems With Application to Geologic CO2 Storage by Zhen Qin, Yingxiang Liu, Fangning Zheng, Behnam Jafarpour

“…The new architecture consists of a physics‐based encoder to construct physically meaningful latent variables, and a residual‐based processor to predict the evolution of the state variables. …”
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Optimizing Patent Prior Art Search: An Approach Using Patent Abstract and Key Terms by Amna Ali, Mohammad Ali Humayun, Liyanage Chandratilak De Silva, Pg Emeroylariffion Abas

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Optimizing colorectal cancer segmentation with MobileViT-UNet and multi-criteria decision analysis by Barun Barua, Genevieve Chyrmang, Kangkana Bora, Manob Jyoti Saikia

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ResNet-Driven Joint Decision-Making for VVC Optimization via Gradient Search by Fangmei Liu, Jiyuan Wang, Qiuwen Zhang

“…Experimental results demonstrate that the proposed algorithm significantly reduces encoding time by 53.17%.At the same time, the BD-BR only increases by 1.38%, showcasing an optimal trade-off between video quality and encoding efficiency.…”
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A Hybrid Discrete Grey Wolf Optimizer to Solve Weapon Target Assignment Problems by Jun Wang, Pengcheng Luo, Xinwu Hu, Xiaonan Zhang

“…All of the running results are compared with those of a discrete particle swarm optimization (DPSO), a genetic algorithm with greedy eugenics (GAWGE), and an adaptive immune genetic algorithm (AIGA). …”
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Probabilistic Principal Component Analysis and Channel Attention for End-to-End Image Compression Optimization by Andri Agustav Wirabudi, Sung-Chang Lim, Woong Lim, Jeongil Seo, Haechul Choi

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Short-term prediction of regional energy consumption by metaheuristic optimized deep learning models by Ngoc-Quang Nguyen, Phuong-Thao-Nguyen Nguyen, Quynh-Chau Truong

“…Results showed that the proposed method outperformed conventional numerical input methods. The optimized model yielded a mean absolute percentage error improvement of 0.5% compared to the default models, indicating that JS is a promising method for achieving the optimal hyperparameters. …”
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Optimization complexity and resource minimization of emitter-based photonic graph state generation protocols by Evangelia Takou, Edwin Barnes, Sophia E. Economou

“…Here, we address these issues using graph theory concepts. We develop optimizers that minimize the number of entangling gates, reducing them by up to 75% compared to naive schemes for moderately sized random graphs. …”
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Comparative Analysis of VGG16 and ResNet50 Model Performence in Cardiac ECG Image Classification by Hanif Rizaqi, Imam Tahyudin

“…The data underwent preprocessing steps including resizing to 224×224 pixels, pixel normalization to a 0–1 range, label encoding, one-hot encoding, and an 80:20 split for training and testing. …”
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Comparative Analysis of Voting and Stacking Ensemble Learning for Heart Disease Prediction: A Machine Learning Approach by Gregorius Airlangga

“…Using a dataset containing clinical and diagnostic attributes, preprocessing steps such as label encoding and standardization were applied to ensure compatibility with machine learning models. …”
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