Showing 21 - 40 results of 5,656 for search 'complex (selection OR detection) (efficient OR efficiency)', query time: 0.27s Refine Results
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    Advanced bioactuator selection for efficient human motion simulation in biohybrid robots using CSF dynamic knowledge by Masfa Nasrullah Ansari, Abdul Razaq, Abdul Wakil Baidar, Dilshad Alghazzawi, Ghaliah Alhamzi

    Published 2025-07-01
    “…Abstract The selection of the most efficient actuator for biohybrid robots necessitates the implementation of precise and reliable decision-making (DM) methods. …”
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    Article
  3. 23

    Efficient Distributed Denial of Service Attack Detection in Internet of Vehicles Using Gini Index Feature Selection and Federated Learning by Muhammad Dilshad, Madiha Haider Syed, Semeen Rehman

    Published 2025-01-01
    “…Our approach is both effective and efficient for detecting DDoS attacks in IoV environments.…”
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    Article
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    Efficient detection and counting method for maize seedling plots by Feiyun Wang, Hanlu Jiang, Jincan Wu, Fupeng Li, Bo Zhao, Wenhua Mao, Chengxu Lv, Liming Zhou, Qingzhong Xu

    Published 2025-08-01
    “…To efficiently detect and count maize seedlings in complex field conditions, this study first developed a sample dataset under diverse backgrounds and lighting scenarios and introduced a data augmentation technique called “M_AUG.” …”
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    Android malware detection via efficient application programming interface call sequences extraction and machine learning classifiers by Tanjie Wang, Yueshen Xu, Xinkui Zhao, Zhiping Jiang, Rui Li

    Published 2023-08-01
    “…To solve these problems, in this study, we propose a novel Android malware detection framework, where we contribute an efficient Application Programming Interface (API) call sequences extraction algorithm and an investigation of different types of classifiers. …”
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    Efficient feature selection based on Gower distance for breast cancer diagnosis by Salwa Shakir Baawi, Mustafa Noaman Kadhim, Dhiah Al-Shammary

    Published 2025-06-01
    “…This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets. …”
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  12. 32

    Efficient Hydrolysis of Sugar Beet Pulp Using Novel Enzyme Complexes by Maria I. Komarova, Margarita V. Semenova, Pavel V. Volkov, Igor A. Shashkov, Alexandra M. Rozhkova, Ivan N. Zorov, Sergei A. Kurzeev, Aidar D. Satrutdinov, Ekaterina A. Rubtsova, Arkady P. Sinitsyn

    Published 2025-01-01
    “…The newly developed strain, as a producer of pectin lyase, arabinofuranosidase, and cellulase complexes, has the potential to be utilized for the bioconversion of sugar beet processing wastes and for the efficient generation of highly concentrated solutions of technical sugars for further implementation in processes of microbial synthesis.…”
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    BGM-YOLO: An accurate and efficient detector for detecting plant disease. by Chenghai Yu, Junhao Xie, Fernandes Jean Adrian Tony

    Published 2025-01-01
    “…The experimental results demonstrate that the BGM-YOLO model achieves a 3.9% improvement in the mean average precision (mAP) over the original model. In crop disease detection tasks, the BGM-YOLO model has higher detection accuracy and a lower false negative rate, confirming its practical value in complex application scenarios.…”
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    An Efficient Group Convolution and Feature Fusion Method for Weed Detection by Chaowen Chen, Ying Zang, Jinkang Jiao, Daoqing Yan, Zhuorong Fan, Zijian Cui, Minghua Zhang

    Published 2024-12-01
    “…Currently, research on vegetable weed detection technology is relatively limited, and existing detection methods still face challenges due to complex natural conditions, resulting in low detection accuracy and efficiency. …”
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    Article
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    Evaluating the Capture Efficiency of Microchannel Plates Through Photoelectron Detection by Mutong Wu, Lingmin Ye, Shangtong Li, Xuan Zhao, Hua Cai, Quan Yu

    Published 2025-06-01
    “…Capture efficiency (CE) is a critical performance parameter for microchannel plates (MCPs), yet its accurate measurement remains challenging. …”
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    Enhanced YOLOv8 with lightweight and efficient detection head for for detecting rice leaf diseases by Bo Gan, Guolin Pu, Weiyin Xing, Lianfang Wang, Shu Liang

    Published 2025-07-01
    “…While YOLO object detection algorithms show strong performance in automated detection, their feature extraction capabilities remain limited in complex agricultural settings. …”
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    Article
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    Advanced Self-Driving Vehicle Model for Complex Road Navigation Using Integrated Image Processing and Sensor Fusion by Kalapraveen Bagadi, Naveen Kumar Vaegae, Visalakshi Annepu, Khaled Rabie, Shafiq Ahmad, Thokozani Shongwe

    Published 2024-01-01
    “…The model integrates state-of-the-art image processing techniques with advanced sensor fusion, utilizing EfficientDet D0 and Haar Cascade object detection models to identify obstacles, road signs, and traffic signals accurately. …”
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    YOLO-SAATD: An efficient SAR airport and aircraft target detector by Daobin Ma, Zhanhong Lu, Zixuan Dai, Yangyue Wei, Li Yang, Haimiao Hu, Wenqiao Zhang, Dongping Zhang

    Published 2025-06-01
    “…While object detection performs well in natural images, it faces challenges in Synthetic Aperture Radar (SAR) images for detecting airports and aircraft due to discrete scattering points, complex backgrounds, and multi-scale targets. …”
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    A Synergistic Approach to Colon Cancer Detection: Leveraging EfficientNet and NSGA-II for Enhanced Diagnostic Performance by Noushin Saba, Afia Zafar, Mohsin Suleman, Kainat Zafar, Shahneer Zafar, Adil Ali Saleem, Hafeez Ur Rehman Siddiqui, Muhammad Iqbal, Syed Sajid Ullah

    Published 2024-01-01
    “…This study proposes an innovative, automated approach to colon cancer diagnosis by integrating advanced machine learning techniques with deep learning architectures. We employed EfficientNet, a state-of-the-art convolutional neural network, to extract intricate features from histopathological images, alongside the Non-dominated Sorting Genetic Algorithm II for optimal feature selection. …”
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