Showing 121 - 140 results of 929 for search '(segment OR regime)', query time: 0.08s Refine Results
  1. 121

    TriCoS: a tri-level class-discriminative co-segmentation method for image classification by Chai, Y, Rahtu, E, Lempitsky, V, Van Gool, L, Zisserman, A

    Published 2012
    “…We introduce TriCoS, a new co-segmentation algorithm that looks at all training images jointly and automatically segments out the most class-discriminative foregrounds for each image. …”
    Conference item
  2. 122

    Restoration and segmentation of old Jawi manuscripts using variational image inpainting and active contour models by Laham, Mohamed Faris, Jumaat, Abdul Kadir, Badarul Azam, Amisha Balkis, Maasar, M. A, Badarul Azam, A. S., Mohammad Sabri, Nur Afiqah Sabirah, Yahaya, Amiratul Munirah, Ismail, Ahmad Thaqif, Abdul Razak, Muhammad Anas

    Published 2024
    “…Recently, the Gaussian Regularization Segmentation (GRS) model has shown effectiveness in intensity inhomogeneity grayscale image segmentation, though it was not designed for corrupted OJM images. …”
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    Article
  3. 123

    Occlusion handling for augmented reality environment using neural network image segmentation: A review. by Ahmad, Muhammad Anwar, Mohd. Suaib, Norhaida, Ismail, Ajune Wanis

    Published 2022
    “…Recently, the advancements of handling occlusions for Augmented Reality (AR) introduces neural network-based image segmentation methods. However, it comes with increased computational costs. …”
    Conference or Workshop Item
  4. 124

    Restoration and Segmentation of Old Jawi Manuscripts using Variational Image Inpainting and Active Contour Models by Badarul Azam, Akmal Shafiq, Jumaat, Abdul Kadir, Badarul Azam, Amisha Balkis, Mohammad Sabri, Nur Afiqah Sabirah, Yahaya, Amiratul Munirah, Ismail, Ahmad Thaqif, Abdul Razak, Muhammad Anas, Maasar, Mohd Azdi, Laham, Mohamed Faris

    Published 2024
    “…Recently, the Gaussian Regularization Segmentation (GRS) model has shown effectiveness in intensity inhomogeneity grayscale image segmentation, though it was not designed for corrupted OJM images. …”
    Get full text
    Article
  5. 125
  6. 126

    Cardiovascular magnetic resonance before invasive coronary angiography in suspected non-ST-segment elevation myocardial infarction by Shanmuganathan, M, Nikolaidou, C, Burrage, MK, Borlotti, A, Kotronias, R, Scarsini, R, Banerjee, A, Terentes-Printzios, D, Pitcher, A, Gara, E, Langrish, J, Lucking, A, Choudhury, R, Luigi De Maria, G, Banning, A, Oxford Acute Myocardial Infarction (OxAMI) Study Investigators, Piechnik, SK, Channon, KM, Ferreira, VM

    Published 2024
    “…<p><strong>Background:</strong> In suspected non–ST-segment elevation myocardial infarction (NSTEMI), this presumed diagnosis may not hold true in all cases, particularly in patients with nonobstructive coronary arteries (NOCA). …”
    Journal article
  7. 127
  8. 128
  9. 129

    Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound by Chen, Yiming

    Published 2024
    “…Unfortunately, current segmentation networks like the UNet lack the precision required for clinical adoption in IVUS workflows. …”
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    Thesis
  10. 130
  11. 131

    Emergent semantic segmentation: training-free dense-label-free extraction from vision-language models by Luo, Jiayun

    Published 2024
    “…PnP-OVSS leverages a VLM with direct text-to-image cross-attention and an image-text matching loss to produce semantic segmentation. However, cross-attention alone tends to over-segment, whereas cross-attention plus GradCAM tend to under-segment. …”
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    Thesis-Master by Research
  12. 132
  13. 133

    Mine yOur owN Anatomy: revisiting medical image segmentation with extremely limited labels by You, C, Dai, W, Liu, F, Min, Y, Dvornek, NC, Li, X, Clifton, DA, Staib, L, Duncan, JS

    Published 2024
    “…In this paper, we introduce a novel semi-supervised 2D medical image segmentation framework termed Mine yOur owNAnatomy (MONA), and make three contributions. …”
    Journal article
  14. 134

    Behind every domain there is a shift: adapting distortion-aware vision transformers for panoramic semantic segmentation by Zhang, J, Yang, K, Shi, H, ReiB, S, Peng, K, Ma, C, Fu, H, Torr, PHS, Wang, K, Stiefelhagen, R

    Published 2024
    “…<p>In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360∘&nbsp;imagery. …”
    Journal article
  15. 135

    Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning by Wan Nor Ashiqin Wan Ali, Wan Ahmad Jaafar Wan Yahaya, Syed Zulkarnain Syed Idrus, Mohd Noorul Fakhri Yaacob

    Published 2024
    “…This study aims to address this gap by examining how learner-paced predefined segments and CT algorithmic thinking can impact TVET students' perceived motivation. …”
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    Article
  16. 136

    From private entrepreneurship to state monopoly: contracting Swiss soldiers for Dutch Service under Ancien Régime Fiscal- Military Practices (1693–1829) by Depreter, M

    Published 2024
    “…This contribution examines Dutch contracting practices to hire Swiss troops during the Ancien Régime, from the first contracts directly negotiated in the Protestant cantons by Petrus Valckenier (1693-1694) during the Nine Years’ War, seizing opportunities arisen from Louis XIV’s revocation of the Edict of Nantes (1685) after a period during which the Dutch seem to have relied on uncertain access to Swiss manpower through French intercession, up to the end of a short-lived revival of Swiss foreign regiments in the newly-instated Kingdom of the Netherlands (1814-1829). …”
    Book section
  17. 137
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  19. 139

    The four facets of self-collection service for e-commerce delivery : conceptualisation and latent class analysis of user segments by Wang, Xueqin, Wong, Yiik Diew, Teo, Chee Chong, Yuen, Kum Fai, Feng, Xuehao

    Published 2021
    “…Based on the conceptualisation, five latent segments of the service are identified, which are labelled as Patrons, Traditionalists, Self-enhancers, Green-lovers and Haters (from the largest to the smallest segment). …”
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    Journal Article
  20. 140