Showing 581 - 600 results of 14,630 for search '"Image"', query time: 0.08s Refine Results
  1. 581

    Three-Dimensional Reconstruction of Tunnel Face Based on Multiple Images by Wenge Qiu, Liao Jian, Yunjian Cheng, Hengbin Bai

    Published 2021-01-01
    “…A novel drawing method for geological sketch has been introduced using multiview photos in this process. The images of tunnel faces are taken from multiple angles, and every two pictures have overlaps. …”
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    Article
  2. 582

    Deformable Image Registration with Inclusion of Autodetected Homologous Tissue Features by Qingsong Zhu, Jia Gu, Yaoqin Xie

    Published 2012-01-01
    “…The proposed method provides a clinically practical solution and should be valuable for various image-guided radiation therapy (IGRT) applications.…”
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    Article
  3. 583

    Fundus Examination of 23,861 Newborns by Digital Imaging in Ningbo by Delin Liu, Jiao Zheng, Yi Lu

    Published 2021-01-01
    “…Fundus examinations were performed on newborns between January 2017 and July 2020 in Ningbo using a RetCam3 or PanoCam LT wide-field digital imaging system. The neonates’ birth weight, gestational age, gender, delivery mode, oxygen intake, and other conditions were recorded. …”
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  4. 584

    CoLR: Classification-Oriented Local Representation for Image Recognition by Tan Guo, Lei Zhang, Xiaoheng Tan, Liu Yang, Zhiwei Guo, Fupeng Wei

    Published 2019-01-01
    “…For this problem, this paper presents a novel representation learning method named classification-oriented local representation (CoLR) for image recognition. The core idea of CoLR is to find the most relevant training classes and samples with test sample by taking the merits of class-wise sparseness weighting, sample locality, and label prior. …”
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  5. 585

    PET imaging of 52Mn labeled DOTATATE and DOTAJR11 by James M. Omweri, Hailey A. Houson, Shannon E. Lynch, Volkan Tekin, Anna G. Sorace, Suzanne E. Lapi

    Published 2025-01-01
    “…Abstract Manganese-52 is gaining interest as an isotope for PET imaging due to its desirable decay and chemical properties for radiopharmaceutical development. …”
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    Ultrasonographic Imaging of Normal and Impacted Omasum in Indian Crossbred Cows by Sheikh Imran, S. P. Tyagi, Amit Kumar, Shivali Sharma

    Published 2011-01-01
    “…These results suggest that ultrasonographic imaging may not be useful in the diagnosis of omasal impaction in Indian crossbred cows, however, additional studies may be warranted.…”
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  8. 588

    An Efficient FPGA Implementation of Optimized Anisotropic Diffusion Filtering of Images by Chandrajit Pal, Avik Kotal, Asit Samanta, Amlan Chakrabarti, Ranjan Ghosh

    Published 2016-01-01
    “…Digital image processing is an exciting area of research with a variety of applications including medical, surveillance security systems, defence, and space applications. …”
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  9. 589

    Human Pose Recognition Based on Depth Image Multifeature Fusion by Haikuan Wang, Feixiang Zhou, Wenju Zhou, Ling Chen

    Published 2018-01-01
    “…A new data set is then established to train the random forest classifier, and a random forest two-way voting mechanism is adopted to classify the pixels on different parts of the human body depth image. Finally, the gravity center of each part is calculated and a reasonable point is selected as the joint to extract human skeleton. …”
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    Article
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    Molecular Imaging Probes for Diagnosis and Therapy Evaluation of Breast Cancer by Qingqing Meng, Zheng Li

    Published 2013-01-01
    “…International Journal of Biomedical Imaging…”
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  13. 593

    DM-KD: Decoupling Mixed-Images for Efficient Knowledge Distillation by Jongkyung Im, Younho Jang, Junpyo Lim, Taegoo Kang, Chaoning Zhang, Sung-Ho Bae

    Published 2025-01-01
    “…To solve this problem, we decouple an input mixed image into two original images and feed them into the teacher model individually. …”
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    Unveiling the Complexity of Medical Imaging through Deep Learning Approaches by Javaid Iqbal Bhat, Novsheena Rasool

    Published 2023-12-01
    “…Recent advancements in deep learning, particularly convolutional networks, have rapidly become the preferred methodology for analyzing medical images, facilitating tasks like disease segmentation, classification, and pattern quantification. …”
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