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  2. arXiv.org
    https://arxiv.org/pdf/2107.06351
    [PDF]

    BRIMA: LOW-OVERHEAD BROWSER-ONLY IMAGE …

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    GitHub - NadineDijkstra/BRIMA: Between-subject variability …
    github.com
    BRIMA Model: Innovation Shapes Radar Future - IEEE
    ieeexplore.ieee.org
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    shutterstock.com
    Brima d'Espoina (brimamodels.com) UCj5ay_5a …
    archive.org
    Stock Photo and Image Portfolio by Brima | Shutterstock
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  3. arXiv.org
    https://arxiv.org/abs/2107.06351

    BRIMA: low-overhead BRowser-only IMage Annotation tool …

  4. ar5iv
    https://ar5iv.labs.arxiv.org/html/2107.06351

    BRIMA: low-overhead Browser-only Image Annotation tool (Preprint)

  5. Studies of site:arxiv.org brima image annotation
    arXiv.org
    BRIMA: low-overhead BRowser-only IMage Annotation tool (Preprint)
    Image annotation and large annotated datasets are crucial parts within the Computer Vision and Artificial Intelligence fields.At the same time, it is well-known and acknowledged by the research community that the image annotation process is challenging,
    Author: Lahtinen, Tuo…
    Published: 2021/07/13
    Cite As: arXiv:2107.06…
    arXiv.org
    Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification
    Magnetic Resonance Imaging (MRI) is a principal diagnostic approach used in the field of radiology to create images of the anatomical and physiological structure of patients. MRI is the prevalent medical imaging practice to find abnormalities in soft
    Author: Brima, Yusuf, …
    Published: 2021/06/14
    Cite As: arXiv:2106.07…
    arXiv.org
    [1210.3448] Notes on image annotation - arXiv.org
    We are under the illusion that seeing is effortless, but frequently the visual system is lazy and makes us believe that we understand something when in fact we don't. Labeling a picture forces us to become aware of the difficulties underlying scene understanding.
    Author: Barriuso, Adel…
    Published: 2012/10/12
    Page Count: 15
    arXiv.org
    Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets
    Data is the engine of modern computer vision, which necessitates collecting large-scale datasets. This is expensive, and guaranteeing the quality of the labels is a major challenge. In this paper, we investigate efficient annotation strategies for collecting
    Author: Liao, Yuan-Ho…
    Published: 2021/04/26
    Cite As: arXiv:2104.12…
    arXiv.org
    [1904.10699v1] The VGG Image Annotator (VIA) - arXiv.org
    Manual image annotation, such as defining and labelling regions of interest, is a fundamental processing stage of many research projects and industrial applications. In this paper, we introduce a simple and standalone manual image annotation tool:
    Author: Dutta, Abhishe…
    Published: 2019/04/24
    Cite As: arXiv:1904.10…
    arXiv.org
    Quick Annotator: an open-source digital pathology based rapid image annotation tool
    Image based biomarker discovery typically requires an accurate segmentation of histologic structures (e.g., cell nuclei, tubules, epithelial regions) in digital pathology Whole Slide Images (WSI). Unfortunately, annotating each structure of interest is
    Author: Miao, Runtian…
    Published: 2021/01/06
    Page Count: 14
    arXiv.org
    The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale
    We present Open Images V4, a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creative Commons Attribution license that allows to share and adapt the material,
    Author: Kuznetsova, Al…
    Published: 2018/11/02
    Cite As: arXiv:1811.009…
    arXiv.org
    [1509.01329] Semantic Amodal Segmentation - arXiv.org
    Common visual recognition tasks such as classification, object detection, and semantic segmentation are rapidly reaching maturity, and given the recent rate of progress, it is not unreasonable to conjecture that techniques for many of these problems will
    Author: Zhu, Yan, Tian…
    Published: 2015/09/04
    Cite As: arXiv:1509.01…
    arXiv.org
    Iconographic Image Captioning for Artworks
    Image captioning implies automatically generating textual descriptions of images based only on the visual input. Although this has been an extensively addressed research topic in recent years, not many contributions have been made in the domain of art
    Author: Cetinic, Eva
    Published: 2021/02/07
    Cite As: arXiv:2102.03…
    arXiv.org
    $\mathrm{SAM^{Med}}$: A medical image annotation framework based on large vision model
    Recently, large vision model, Segment Anything Model (SAM), has revolutionized the computer vision field, especially for image segmentation. SAM presented a new promptable segmentation paradigm that exhibit its remarkable zero-shot generalization ability.
    Author: Wang, Chengl…
    Published: 2023/07/11
    Cite As: arXiv:2307.05…
    arXiv.org
    Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment
    We introduce a method to train vision-language models for remote-sensing images without using any textual annotations. Our key insight is to use co-located internet imagery taken on the ground as an intermediary for connecting remote-sensing images and
    Author: Mall, Utkarsh, …
    Published: 2023/12/12
    Cite As: arXiv:2312.06…
  6. arXiv.org
    https://arxiv.org/pdf/2104.08885
    [PDF]

    A survey of image labelling for computer vision applications

    Tags:
    Image Annotation
    Publish Year:2021
    Computer Vision
  7. arXiv.org
    https://arxiv.org/abs/2106.07333

    Deep Transfer Learning for Brain Magnetic Resonance Image …

    Tags:
    Publish Year:2021
    Machine Learning
    Deep Transfer Learning Models
  8. arXiv.org
    https://arxiv.org/pdf/2312.10600.pdf
    [PDF]

    How to Efficiently Annotate Images for Best-Performing Deep …

  9. arXiv.org
    https://arxiv.org/abs/1210.3448

    [1210.3448] Notes on image annotation - arXiv.org

    Tags:
    Image Annotation Tool Open-Source
    Image Annotation Work Online
  10. arXiv.org
    https://arxiv.org/abs/2104.12690

    Towards Good Practices for Efficiently Annotating Large-Scale …

    Tags:
    Image Annotation
    Publish Year:2021
    Computer Vision
    Machine Learning
  11. arXiv.org
    https://arxiv.org/abs/1904.10699v1

    [1904.10699v1] The VGG Image Annotator (VIA) - arXiv.org

    Tags:
    Image Annotation
    Abhishek Dutta, Andrew Zisserman
    Publish Year:2019
  12. arXiv.org
    https://arxiv.org/pdf/1602.07332
    [PDF]

    Connecting Language and Vision Using Crowdsourced …

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    Publish Year:2017
  13. arXiv.org
    https://arxiv.org/html/2306.12189v2

    Annotating Ambiguous Images: General Annotation Strategy for …

  14. arXiv.org
    https://arxiv.org/html/2312.10600v2

    How to Efficiently Annotate Images for Best-Performing Deep …

  15. arXiv.org
    https://arxiv.org/pdf/2109.02688v1
    [PDF]

    Rethinking Crowdsourcing Annotation: Partial Annotation …

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    Publish Year:2021
    Jianzhe Lin, Tianze Yu, Z. Jane Wang
  16. arXiv.org
    https://arxiv.org/abs/2101.02183

    Quick Annotator: an open-source digital pathology based rapid …

    Tags:
    Publish Year:2021
    arXiv:2101.02183 [eess.IV
    Image and Video Processing (eess.IV)
  17. arXiv.org
    https://arxiv.org/abs/1811.00982

    [1811.00982] The Open Images Dataset V4: Unified image …

    Tags:
    Publish Year:2018
  18. arXiv.org
    https://arxiv.org/pdf/1912.10107.pdf
    [PDF]

    arXiv:1912.10107v1 [cs.CV] 20 Dec 2019

    Tags:
    Image Annotation
    Datasets
  19. arXiv.org
    https://arxiv.org/pdf/1904.10699v1
    [PDF]

    The VGG Image Annotator (VIA) - arXiv.org

  20. arXiv.org
    https://arxiv.org/abs/1509.01329

    [1509.01329] Semantic Amodal Segmentation - arXiv.org

    Tags:
    Image Annotation
    Publish Year:2015
    arXiv:1509.01329 [cs.CV
  21. arXiv.org
    https://arxiv.org/abs/2102.03942

    [2102.03942] Iconographic Image Captioning for Artworks - arXiv.org

    Tags:
    Publish Year:2021
    Automated Image Captioning
    Caption For Artistic Pic
  22. arXiv.org
    https://arxiv.org/abs/2404.08951

    [2404.08951] Constructing and Exploring Intermediate Domains …

  23. arXiv.org
    https://arxiv.org/html/2401.14159v1

    Grounded SAM: Assembling Open-World Models for Diverse …

  24. arXiv.org
    https://arxiv.org/abs/2307.05617

    [2307.05617] $\mathrm {SAM^ {Med}}$: A medical image …

    Tags:
    Image Annotation
    arXiv:2307.05617 [cs.CV
  25. arXiv.org
    https://arxiv.org/abs/2312.06960

    Remote Sensing Vision-Language Foundation Models without …