The analysis of landscape design and plant selection under deep learning by Lian Li, JiYon Lee

“…Abstract This paper explores the application of deep learning (DL) techniques in landscape design and plant selection, aiming to enhance design efficiency and quality through automated plant leaf image recognition (PLIR). …”
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Data selection strategies for minimizing measurement time in materials characterization by Alexander Liehr, Kristina Dingel, Daniel Kottke, Sebastian Degener, David Meier, Bernhard Sick, Thomas Niendorf

“…Obviously, this kind of approach is extremely time-consuming and, eventually, not efficient. The present study highlights that specific selection strategies, taking into account the prevailing microstructure of the alloy in focus, can decrease counting times in X-ray energy dispersive diffraction experiments without any detrimental effect on data quality for the subsequent analysis. …”
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EIM: A Novel Evolutionary Influence Maximizer in Complex Networks by Vahideh Sahargahi, Vahid Majidnezhad, Saeid Taghavi Afshord, Yasser Jafari

“…This article introduces a double-chromosome evolutionary algorithm to tackle this challenge efficiently. This method introduces a smart operator for stochastic selection based on the node degree to initialize the primary solutions. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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Complex interspecific and intersexual patterns of wing design in Heliconius butterflies by Luis Mendoza-Cuenca

“…The results highlight the complexity of traits involved in the evolutionary designs of wings in Lepidoptera.…”
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A YOLO-Based Method for Head Detection in Complex Scenes by Ming Xie, Xiaobing Yang, Boxu Li, Yingjie Fan

“…Secondly, it was found in practical operations that the original IoU function has a serious problem with overlapping detection in complex scenes. There is an IoU function that can ensure that the final selection boxes cover the object as accurately as possible without overlapping. …”
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Nonlocal flat optics for size-selective image processing and denoising by Sandeep Kumar Chamoli, Chunqi Jin, Yandong Fan, Mehdi Kiani, Heedong Goh, Chen Huang, Shuyu Guo, Yuntong Wang, Fei Zhu, Guohua Xing, Bo Li, Tian Bai, Andrea Alù, Wei Li

“…So far, the proposed devices have been focusing on canonical operations, such as differentiations to perform edge detection across all objects in a complex scene. Yet, undesired background noise and clutter can hinder such operations, requiring target selection with digital post-processing which inherently limits the overall accuracy, efficiency and speed. …”
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A Distributed Coalition Selection of Distribution Centers for Delivery Stations by Fan Wu, Ming Yu, Jingya Zhang, Yicheng Fan, Ming Li

“…Unlike centralized optimization methods, the proposed approach enables real-time decision-making with reduced computational complexity while maintaining both system-wide efficiency and individual delivery station satisfaction. …”
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ANALYSIS OF SELECTED TRANSPORTATION NETWORK STRUCTURES BASED ON GRAPH MEASURES by Renata ŻOCHOWSKA, Piotr SOCZÓWKA

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Bio-Inspired Swarm Confrontation Algorithm for Complex Hilly Terrains by He Cai, Fu Ma, Ruifeng Ni, Weiyuan Xu, Huanli Gao

“…This paper explores a bio-inspired swarm confrontation algorithm specifically designed for complex hilly terrains in the context of electronic games. …”
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Enhancing Crack Segmentation Network with Multiple Selective Fusion Mechanisms by Yang Chen, Tao Yang, Shuai Dong, Like Wang, Bida Pei, Yunlong Wang

“…Furthermore, the proposed MSF-CrackNet also significantly reduces computational complexity, with only 2.39 million parameters and 8.58 GFLOPs, making it a practical and efficient solution for real-world crack detection tasks, especially in scenarios with limited computational resources.…”
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Congruent Learning for Self-Regulated Federated Learning in 6G by Jalil Taghia, Farnaz Moradi, Hannes Larsson, Xiaoyu Lan, Adam Orucu, Masoumeh Ebrahimi, Andreas Johnsson

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Angle Modulated Artificial Bee Colony Algorithms for Feature Selection by Gürcan Yavuz, Doğan Aydin

“…To present the effectiveness of the problem presentation with angle modulation and to determine the efficiency of the proposed method, six variants of Artificial Bee Colony (ABC) algorithms employ angle modulation for feature selection. …”
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AIN-Based Action Selection Mechanism for Soccer Robot Systems by Yin-Tien Wang, Zhi-Jun You, Chia-Hsing Chen

“…This AIN-based action-select provides an efficient and robust algorithm for robot role selection. …”
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Firefly Algorithm based Feature Selection for Arabic Text Classification by Souad Larabi Marie-Sainte, Nada Alalyani

“…The results confirm the efficiency of the proposed feature selection method in improving Arabic Text Classification accuracy. …”
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Scene categorization by Hessian-regularized active perceptual feature selection by Junwu Zhou, Fuji Ren

“…Abstract Decoding the semantic categories of complex sceneries is fundamental to numerous artificial intelligence (AI) infrastructures. …”
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Quality Improvement in Critical Care: Selection and Development of Quality Indicators by Carla A. Chrusch, Claudio M. Martin, The Quality Improvement in Critical Care Project

“…Caring for critically ill patients is complex and resource intensive. An approach to monitor and compare the function of different intensive care units (ICUs) is needed to optimize outcomes for patients and the health system as a whole. …”
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Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning by Łukasz Jeleń, Izabela Stankiewicz-Antosz, Maria Chosia, Michał Jeleń

“…The results demonstrate that optimized feature sets, paired with SVM classifiers, achieve classification performance comparable to those of CNNs while significantly reducing computational complexity. This finding underscores the potential of feature reduction techniques in creating efficient diagnostic frameworks. …”
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Investigation and selection of initial materials as possible sources for obtaining sorbents by I. A. Таgaev, S. U. Tursunova, L. S. Andriyko

“… The information about selection of initial materials based on bentonite, brown coal and technical soot for obtaining new sorbents is presented in this article. …”
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Selective electrocatalytic nitrate reduction to dinitrogen: Mechanisms, catalysts, and challenges by Jiayu Chen, Anni Wu, Yongfeng Xie, Yumin Zhang, Hu Zheng, Wei Teng

“…While extensive research has focused on ammonia production, selective N2 production remains challenging due to complex pathways, limitations in detection, and the difficulty of controlling reaction on the electrocatalysts. …”
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