Showing 1,341 - 1,360 results of 2,900 for search '(feature OR features) parameters (computation OR computational)', query time: 0.22s Refine Results
  1. 1341

    TongueNet: a multi-modal fusion and multi-label classification model for traditional Chinese Medicine tongue diagnosis by Lijuan Yang, Lijuan Yang, Qiumei Dong, Da Lin, Xinliang Lü

    Published 2025-04-01
    “…Moreover, TongueNet contains only 32.1 M parameters, significantly reducing computational resource requirements while maintaining high diagnostic performance. …”
    Get full text
    Article
  2. 1342

    Investigating multi-directional flow dynamics in three-way ball valves: a CFD-based study by Amol Dhumal, Nitin Ambhore, Gaurav Sanap, Tanmay Patil, Vishal Sanap, Aryan Kadu

    Published 2025-05-01
    “…Abstract The objective of this study is to analyze a three-way ball valve using computational fluid dynamic simulations in ANSYS Fluent to achieve better flow control and improve the efficiency of the system. …”
    Get full text
    Article
  3. 1343

    Impact of Direct Soil Moisture and Revised Soil Moisture Index Methods on Hydrologic Predictions in an Arid Climate by Milad Jajarmizadeh, Sobri bin Harun, Shamsuddin Shahid, Shatirah Akib, Mohsen Salarpour

    Published 2014-01-01
    “…The results showed that the sensitive parameters for the SMI method are land-use and land-cover features. …”
    Get full text
    Article
  4. 1344

    Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

    Published 2025-07-01
    “…To improve the recognition accuracy of small targets, a bidirectional feature pyramid network (BiFPN) is integrated, enabling the model to capture small target features more precisely. …”
    Get full text
    Article
  5. 1345

    A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

    Published 2025-07-01
    “…To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. TBiGNet features an encoder–decoder architecture that outperforms traditional Transformer models by achieving over 15% higher accuracy while reducing computational load, memory access, and parameter size by more than 98%. …”
    Get full text
    Article
  6. 1346

    YOLOv10-kiwi: a YOLOv10-based lightweight kiwifruit detection model in trellised orchards by Jie Ren, Wendong Wang, Yuan Tian, Jinrong He

    Published 2025-08-01
    “…This replacement enables parallel processing and enhances feature extraction efficiency. By combining heterogeneous kernels in sequence, C2fDualHet captures both local and global features while significantly lowering parameter count and computational cost. …”
    Get full text
    Article
  7. 1347

    A lightweight trichosanthes kirilowii maxim detection algorithm in complex mountain environments based on improved YOLOv7-tiny. by Zhongjian Xie, Xinwei Chen, Weilin Wu, Yao Xiao, Yuanhang Li, Yaya Zhang, ZhuXuan Wan, Weiqi Chen

    Published 2025-01-01
    “…However, the environmental characteristics of brightness variation, inter-plant occlusion, and motion-induced blurring during harvesting operations, detection algorithms face excessive parameters and high computational intensity. Accordingly, this study proposes a lightweight T.Kirilowii detection algorithm for complex mountainous environments based on YOLOv7-tiny, named KPD-YOLOv7-GD. …”
    Get full text
    Article
  8. 1348

    A lightweight MHDI-DETR model for detecting grape leaf diseases by Zilong Fu, Lifeng Yin, Can Cui, Yi Wang

    Published 2024-12-01
    “…The original residual backbone network was improved using the MobileNetv4 network, significantly reducing the model’s computational requirements and complexity. Additionally, a lightSFPN feature fusion structure is presented, combining the Hierarchical Scale Feature Pyramid Network with the Dilated Reparam Block structure design from the UniRepLKNet network. …”
    Get full text
    Article
  9. 1349

    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
    “…This network has the advantages of simple structure and high lightweight, which effectively reduces the amount of calculation and parameters of the model. Then the feature extraction structure of the YOLOv8 neck is replaced with the BiFPN (Bi-directional Feature Pyramid Network) structure. …”
    Get full text
    Article
  10. 1350
  11. 1351

    ShadowFPN-YOLO: A Real-Time NMS-Free Detector for Remote Sensing Ship Detection by Xiao Yang, Ahmad Sufril Azlan Mohamed, Chuanchuan Wang

    Published 2025-01-01
    “…Experimental results demonstrate the strong performance of our method, achieving mAP values of 55.70 at 430 FPS on the DIOR-Ship dataset and 55.85 at 497 FPS on the HRSID dataset, all while maintaining the fewest parameters and the lowest computational cost compared to the latest YOLO models. …”
    Get full text
    Article
  12. 1352

    A lightweight Xray-YOLO-Mamba model for prohibited item detection in X-ray images using selective state space models by Kai Zhao, Shufan Peng, Yujin Li, Tianliang Lu

    Published 2025-04-01
    “…Despite significant advancements in deep learning, challenges such as feature extraction, object occlusion, and model complexity remain. …”
    Get full text
    Article
  13. 1353

    ConvTransNet-S: A CNN-Transformer Hybrid Disease Recognition Model for Complex Field Environments by Shangyun Jia, Guanping Wang, Hongling Li, Yan Liu, Linrong Shi, Sen Yang

    Published 2025-07-01
    “…This model operates with only 25.14 million parameters, a computational load of 3.762 GFLOPs, and an inference time of 7.56 ms. …”
    Get full text
    Article
  14. 1354
  15. 1355
  16. 1356

    CAFNet: Cross-Modal Adaptive Fusion Network With Attention and Gated Weighting for RGB-T Semantic Segmentation by Meili Fu, Huanliang Sun, Zhihan Chen, Lulin Wei

    Published 2025-01-01
    “…The experimental results show that CAFNet achieves a 60.1% mIoU on the MFNet dataset, which is 1.2% higher than that of EAEFNet (58.9% mIoU), and the computational cost (110.61G FLOPs) and parameter count (68.13 M) are also reduced by 25% and 66.1%, respectively. …”
    Get full text
    Article
  17. 1357
  18. 1358

    Stability Enhancement of Inverter-Based Microgrids Using Optimized Neural Networks by PANG Kai, TANG Zhiyuan, GAO Hongjun, LIU Youbo, LIU Junyong

    Published 2025-08-01
    “…To enhance the stability of inverter-based MGs,this study introduces a novel data-driven method for the coordinated and rapid local adjustment of inverter multicontrol parameters. [Methods] An offline eigenvalue-based optimization problem was formulated to compute the optimal multicontrol parameters using the osprey optimization algorithm(OOA)under various operating conditions. …”
    Get full text
    Article
  19. 1359

    A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

    Published 2024-11-01
    “…The Fuding white tea bud image dataset was established by collecting Fuding white tea images; then the lightweight network ShuffleNetV2 was used to replace the YOLOV5 backbone network; the up-sampling algorithm of YOLOV5 was optimized by using CARAFE modular structure, which increases the sensory field of the network while maintaining the lightweight; then BiFPN was used to achieve more efficient multi-scale feature fusion; and the introduction of the parameter-free attention SimAm to enhance the feature extraction ability of the model while not adding extra computation. …”
    Get full text
    Article
  20. 1360

    DCD-FPI: A Deformable Convolution-Based Fusion Network for Unmanned Aerial Vehicle Localization by Yufei He, Feiyang Chen, Jiahao Chen, Jiqi Fan, Enhui Zheng

    Published 2024-01-01
    “…Moreover, our model reduces computational complexity from 14.28 GFLOPS to 11.54 GFLOPS and parameter quantity from 14.76 M to 13.96 M.…”
    Get full text
    Article