Enhancing Camera Source Identification: A Rapid Algorithm with Enhanced Discriminative Power by Zhimao Lai, Lijuan Cheng, Renhai Feng

“…Compared to the traditional brute-force search algorithm (BFSA), our method significantly reduces computational complexity in large-scale databases, optimizing from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mi>N</mi><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo form="prefix">log</mo><mi>N</mi><mo>)</mo></mrow></semantics></math></inline-formula>, where <i>n</i> is the length of the fingerprint, and <i>N</i> is the number of fingerprints in the database. …”
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A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…This estimation is challenging due to computational complexity and the risk of optimization errors, which can hinder reliable performance predictions. …”
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Design of Super Resolution and Fuzzy Deep Learning Architecture for the Classification of Land Cover and Landsliding Using Aerial Remote Sensing Data by Junaid Ali Khan, Muhammad Attique Khan, Mohammed Al-Khalidi, Dina Abdulaziz AlHammadi, Areej Alasiry, Mehrez Marzougui, Yudong Zhang, Faheem Khan

“…Moreover, the stability and computational complexity of the presented architecture are computed on 50 independent runs. …”
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A Comparison of Classification Algorithms for Predicting Dis-tinctive Characteristics in Fine Aroma Cocoa Flowers Using WE-KA Modeler by Daniel Tineo, Yuriko S. Murillo, Mercedes Marín, Darwin Gomez, Victor H. Taboada, Malluri Goñas, Lenin Quiñones Huatangari

“…The algorithms Simple Logistic and LMT were the most accurate and specific, while Naive Bayes was the most efficient in terms of computational complexity for model building. This research provides a comprehensive overview of the use of machine learning to analyze functional traits of flowers that most influence cocoa genetic diversity. …”
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A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition by Jiawen Li, Guanyuan Feng, Chen Ling, Ximing Ren, Xin Liu, Shuang Zhang, Leijun Wang, Yanmei Chen, Xianxian Zeng, Rongjun Chen

“…The proposed method achieves 84.62% and 82.48% accuracy in arousal and valence classification tasks, respectively, indicating its effectiveness in reducing data dimensionality and computational complexity while maintaining an accuracy of over 80%. …”
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A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario by Amir Masoud Molaei, Bijan Zakeri, Seyed Mehdi Hosseini Andargoli, Muhammad Ali Babar Abbasi, Vincent Fusco, Okan Yurduseven

“…Special attention is given to technical issues such as aperture loss, computational complexity, and hardware considerations. The paper discusses the various sources of noise in the mentioned scenario and highlights the importance of modeling noise accurately for effective estimation. …”
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&#x03F5;-Confidence Approximately Correct (&#x03F5;-CoAC) Learnability and Hyperparameter Selection in Linear Regression Modeling by Soosan Beheshti, Mahdi Shamsi

“…Drawbacks of these methods include introducing new hyperparameters with their own new challenges and uncertainties, potential increase of the computational complexity or requiring large set of training data sets. …”
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MSCPNet: A Multi-Scale Convolutional Pooling Network for Maize Disease Classification by Mehdhar S. A. M. Al-Gaashani, Reem Alkanhel, Muthana Ali Salem Ali, Mohammed Saleh Ali Muthanna, Ahmed Aziz, Ammar Muthanna

“…These models also suffer from high computational complexity when deeper layers are introduced to handle fine-grained details. …”
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Novel Pythagorean fuzzy score function to optimize fuzzy transportation models by Ritu, Tarun Kumar, Jahnvi, Kapil Kumar, Nitesh Dhiman, M.K. Sharma

“…Also, the proposed score function integrates these interval values to quantify and rank the alternatives more effectively.However, a notable trade-off is the increased computational complexity due to the use of interval values in the membership and non-membership functions, particularly in larger-scale transportation problems. …”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…However, the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs. Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues. …”
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A lightweight wheat ear counting model in UAV images based on improved YOLOv8 by Ruofan Li, Xiaohua Sun, Kun Yang, Zhenxue He, Zhenxue He, Xinxin Wang, Xinxin Wang, Chao Wang, Chao Wang, Bin Wang, Fushun Wang, Fushun Wang, Hongquan Liu, Hongquan Liu

“…Additionally, a lightweight dynamic upsampler, Dynamic Sample (DySample), is introduced to decrease computational complexity of the upsampling process by dynamically adjusting interpolation positions. …”
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Grape Recognition and Localization Method Based on 3C-YOLOv8n and Depth Camera by LIU Chang, SUN Yu, YANG Jing, WANG Fengchao, CHEN Jin

“…This enhancement increased the receptive field and guided the reconstruction process based on input features while maintaining low parameter and computational complexity, thereby forming the 3C-YOLOv8n model. …”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…However, adding a P2 layer may increase computational complexity and resource consumption, so the overall performance and resource consumption of the model must be carefully balanced. …”
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BDC-DAL: A new algorithm using blueprint difference convolution and dual auxiliary supervision for lightweight face anti-spoofing(BDC-DAL：基于蓝图差分卷积和双重辅助监督的轻量化人脸活体检测算法)... by 叶继华(YE Jihua), 梁芳昕(LIANG Fangxin), 王超(WANG Chao), 肖顺杰(XIAO Shunjie), 宗义(ZONG Yi), 江爱文(JIANG Aiwen)

“…Most current face anti-spoofing methods employ deep convolutional neural networks, and although these systems can provide excellent detection performance, they often involve large number of parameters and computational complexity, which limits their application on resource-limited devices. …”
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MSH-YOLOv8: Mushroom Small Object Detection Method with Scale Reconstruction and Fusion by YE Dapeng, JING Jun, ZHANG Zhide, LI Huihuang, WU Haoyu, XIE Limin

“…Additionally, the normalization-based attention module (NAM) was employed to improve performance without compromising detection speed or computational complexity. To further enhance training efficacy and convergence speed, the original loss function CIoU was replaced with wise-intersection over union (WIoU) Loss. …”
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Efficient Prediction of Network Traffic for Real-Time Applications by Muhammad Faisal Iqbal, Muhammad Zahid, Durdana Habib, Lizy Kurian John

“…Comparison of accuracy and cost, both in terms of computation complexity and power consumption, is presented. …”
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Delay constraint minimum interruption routing algorithm for mobile satellite network by ZHANG Tao, LIU Zhong-kan, ZHANG Jun

“…By the analysis of the characteristics of mobile satellite network,such as a long delay and a topological time-varying,a novel satellite network delay constraint optimal path（SDCOP）algorithm,which could obtain a path to sat-isfy the delay constraint condition as well as the minimization of interruption during the service,was proposed.This algo-rithm exploits the predictive nature of connectivity changes of time-varying topological to decrease the influence in the QoS routing performance caused by the handover.Besides,it has a low computing complexity to adapt to the restricted computing capability of satellite equipments.Correlative simulation indicates that this novel algorithm is superior to other current algo-rithm in respect of computing complexity,service blocking probability and interrupting probability etc.…”
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Single-channel blind separation of co-frequency modulated signals based on Gibbs sampler by Yong YANG, Dong-ling ZHANG, Hua PENG, Shi-long TU

“…A Gibbs-sampler-based separation algorithm was proposed for single-channel co-frequency digital-modulated signals，which were received in non-cooperative ways.The probability density samples of unknown symbol sequences can be obtained by statistic method，and the computation complexity was not growing exponentially with the increase of channel order.With special emphasis on the separation algorithms of single pair of symbols，multiple pair of symbols and the tracking of channel responses.Moreover，the separation performance between Gibbs sampler and per-survivor processing(PSP) algorithm were analyzed and compared in detail.Simulation results show that，compared with PSP algorithm with L=4 for two co-frequency QPSK-modulated signals，Gibbs sampler can be nearly 17 times lower in computation complexity when the approximately performance is obtained.…”
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Phase retrieval for block sparsity based on adaptive coupled variational Bayesian learning by Di Zhang, Yimao Sun, Siqi Bai, Qun Wan

“…Simulations indicate that the proposed algorithm outperforms the existing methods in success rate, noise‐robustness, and signal detection rate in large‐scale cases with acceptable computation complexity.…”
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Recognition method of digital modulation signals over non-Gaussian noise in cognitive radio by Ming-qian LIU, Bing-bing LI, Chao-feng CAO, Zhao LI

“…In cognitive radio system,the traditional methods of digital modulation signals recognition with Alpha stable distribution noise have the problems of poor performance and high computation complexity.A novel recognition method based on correlation coefficient of fractional lower order cyclic spectrum was proposed to solve this problem.The method extracts the recognition characteristic parameters which are five correlation coefficients of the fractional lower order cyclic spectrum’s section and frequency spectrum’s section and projection planes of both,and then decision tree was used as a classifier to achieve digital modulation signals recognition.Simulation results show that the proposed method not only has higher recognition rates and better robustness but also has lower computation complexity in an Alpha stable distribution noise environment,which is more suitable for cognitive radio system.…”
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