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Showing 261 - 280 results of 1,810 for search '(( sources detection functions ) OR (( resource OR resources) detection function ))', query time: 0.24s Refine Results
  1. 261

    Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

    Published 2025-05-01
    “…The proposed approach is efficient and feasible, offering a more stable and accurate disease detection system while utilizing fewer resources. This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques.…”
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    Article
  2. 262

    Ultra-sensitive terahertz photonic crystal fiber sensor for detection of tuberculosis by Md. Safiul Islam, A.H.M. Iftekharul Ferdous, Abdullah Al Mamun, Md. Shamim Anower, Md. Jakir Hossen, Syed Udoy Ahmed

    Published 2025-06-01
    “…This sensing unit under consideration can function within the terahertz frequency range. Consequently, it serves as a valuable resource for healthcare providers, enhancing their diagnostic capabilities for prompt treatment and improved patient outcomes. …”
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    Article
  3. 263

    Pavement Disease Visual Detection by Structure Perception and Feature Attention Network by Bin Lv, Shuo Zhang, Haixia Gong, Hongbo Zhang, Bin Dong, Jianzhu Wang, Cong Du, Jianqing Wu

    Published 2025-01-01
    “…Balancing detection performance and computational efficiency is critical for sustainable pavement disease detection in energy-constrained scenarios. …”
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    Article
  4. 264

    LiteTom-RTDETR: A Lightweight Real-Time Tomato Detection System for Plant Factories by Wenshuai Liu, Qingzheng Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qiang Liu, Yuxiang Tian

    Published 2025-06-01
    “…The accuracy and speed of tomato detection were increased to facilitate fully automated harvesting by improving the Real-Time Detection Transformer (RTDETR) to develop a new lightweight tomato detection model called LiteTom-RTDETR. …”
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    Article
  5. 265

    Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

    Published 2024-01-01
    “…Moreover, we also propose a detection feature pyramid loss function to more accurately restore object features. …”
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    Article
  6. 266
  7. 267

    A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

    Published 2024-01-01
    “…However, traditional methods of tire defect detection have encountered problems such as slow detection speed, complex tire defect backgrounds, and limited hardware resources. …”
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    Article
  8. 268

    Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

    Published 2025-03-01
    “…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. Through this pruning strategy, the model further reduces its dependence on computing resources while maintaining key performance. …”
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    Article
  9. 269

    Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

    Published 2024-11-01
    “…In addition, the need for comprehensive train detection including pantograph-catenary systems and running gears, lead to an increased number of on-board devices, resulting in fewer computational resources available for each detection system, and complicating equipment installation and maintenance. …”
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    Article
  10. 270

    Vulnerability detection method for blockchain smart contracts based on metamorphic testing by Jinfu CHEN, Zhenxin WANG, Saihua CAI, Qiaowei FENG, Yuhao CHEN, Rongtian XU, KwakuKudjo Patrick

    Published 2023-10-01
    “…Aimed at the defects of existing test methods, a vulnerability detection method for blockchain smart contracts based on metamorphic testing was proposed, which could generate test cases for specific functions in blockchain smart contracts to detect possible vulnerabilities.According to the possible security vulnerabilities, different metamorphosis relationships were designed and then metamorphic testing was performed.Through verifying whether the metamorphic relationship between the source test case and the subsequent test case was satisfied, whether the smart contract had related security vulnerabilities was judged.The experimental results show that the proposed method can effectively detect the security vulnerabilities in the smart contracts.…”
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    Article
  11. 271

    An investigation of the distribution of gaze estimation errors in head mounted gaze trackers using polynomial functions by Diako Mardanbegi, Andrew T. N. Kurauchi, Carlos H. Morimoto

    Published 2018-06-01
    “…In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions. Using simulated scenarios, we describe effects of four different sources of error: interpolation, extrapolation, parallax, and radial distortion. …”
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  12. 272

    A Route to the Colorimetric Detection of Alpha-Fetoprotein Based on a Smartphone by Junjie Liu, Qingfubo Geng, Zhaoxin Geng

    Published 2024-08-01
    “…Alpha-fetoprotein (AFP) is a key marker for early cancer detection and assessment. However, the current detection methods struggle to balance accuracy with the need for decentralized medical treatment. …”
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    Article
  13. 273

    Interpretable Chinese Fake News Detection With Chain-of-Thought and In-Context Learning by Bingyi Liu, Anqi Wang, Chengqian Xia

    Published 2025-01-01
    “…The spread of fake news through on-line platforms poses a significant threat to public trust and social stability, especially in resource-constrained Chinese domains. Existing Fake News Detection (FND) models often lack transparency, functioning as “black boxes” that limit their practical utility. …”
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  14. 274
  15. 275

    A DFT insight into the potential of cycloparaphenylenes as efficient sensors for detecting Paracetamol by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

    Published 2025-03-01
    “…This study presents a computational investigation into the sensing capabilities of methylene-bridged [n]cycloparaphenylene ([n]MCPP, where n= 6, 8, and 10) nanorings for the detection of paracetamol using density functional theory (DFT) calculations. …”
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  16. 276

    TEDVIL: Leveraging Transformer-Based Embeddings for Vulnerability Detection in Lifted Code by Gary A. McCully, John D. Hastings, Shengjie Xu

    Published 2025-01-01
    “…Notably, these results are achieved when the embedding model is trained with a dataset of just 48,000 functions, demonstrating effectiveness in resource-constrained settings. …”
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    Article
  17. 277

    Synthesis and properties of carbon quantum dots as an antimicrobial agent and detection of ciprofloxacin by Fangzhou Shen, Zhaoyang Lu, Kangli Yan, Kang Luo, Shuchen Pei, Pu Xiang

    Published 2025-08-01
    “…This study introduces a novel approach for the fabrication of N-CQDs derived from natural botanical sources, underscoring their potential dual functionality as fluorescent sensors and antimicrobial materials.…”
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  18. 278

    A review of deep learning models to detect malware in Android applications by Elliot Mbunge, Benhildah Muchemwa, John Batani, Nobuhle Mbuyisa

    Published 2023-12-01
    “…Android applications are indispensable resources that facilitate communication, health monitoring, planning, data sharing and synchronization, social interaction, business and financial transactions. …”
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  19. 279
  20. 280

    LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

    Published 2025-06-01
    “…These results underscore the model’s feasibility and robustness compared to other state-of-the-art object detection models. The source code and dataset will be available through the GitHub repository.…”
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