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Topic modelling on Instagram hashtags: An alternative way to Automatic Image Annotation?
International Workshop on Semantic and Social Media Adaptation and Personalization, 2018Automatic Image Annotation (AIA) is the process of assigning tags to digital images without the intervention of humans. Most of the modern automatic image annotation methods are based on the learning by example paradigm.
Argyris Argyrou +2 more
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2006 International Conference on Image Processing, 2006
We propose an unsupervised approach to segment color images and annotate its regions. The annotation process uses a multi-modal thesaurus that is built from a large collection of training images by learning associations between low-level visual features and keywords.
Hichem Frigui, Joshua Caudill
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We propose an unsupervised approach to segment color images and annotate its regions. The annotation process uses a multi-modal thesaurus that is built from a large collection of training images by learning associations between low-level visual features and keywords.
Hichem Frigui, Joshua Caudill
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Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
European Conference on Computer Vision, 2020Few-shot semantic segmentation (FSS) has great potential for medical imaging applications. Most of the existing FSS techniques require abundant annotated semantic classes for training.
C. Ouyang +5 more
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Medical Image Annotation Based on Deep Transfer Learning
2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2018The using of deep learning method belongs to the application and research of artificial intelligence technology in medical field for assisting medical image information processing.
Shoulin Yin, Jing Bi
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3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2016This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this method: (1) In a semi-automated setup, the user annotates some slices in the volume to be ...
Özgün Çiçek +4 more
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From Image Annotation to Image Description
2012In this paper, we address the problem of automatically generating a description of an image from its annotation. Previous approaches either use computer vision techniques to first determine the labels or exploit available descriptions of the training images to either transfer or compose a new description for the test image. However, none of them report
Ankush Gupta, Prashanth Mannem
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Annotating Images by Mining Image Search
2011Although it has been studied for years by computer vision and machine learning communities, image annotation is still far from practical. In this chapter, the authors propose a novel attempt of modeless image annotation, which investigates how effective a data-driven approach can be, and suggest annotating an uncaptioned image by mining its search ...
Xin-Jing Wang +3 more
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Semi-automatic Image Annotation
2013High quality ground truth data is essential for the development of image recognition systems. General purpose datasets are widely used in research, but they are not suitable as training sets for specialized real-world recognition tasks. The manual annotation of custom ground truth data sets is expensive, but machine learning techniques can be applied ...
Julia Moehrmann, Gunther Heidemann
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2013
Image retrieval most commonly uses text-based search, which requires the availability of image annotations. As digital photos are growing rapidly in number, making manual image annotation impractical, the need for automatic image annotation is evident.
Randi Karlsen, Anders Andersen
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Image retrieval most commonly uses text-based search, which requires the availability of image annotations. As digital photos are growing rapidly in number, making manual image annotation impractical, the need for automatic image annotation is evident.
Randi Karlsen, Anders Andersen
openaire +1 more source
The image annotation algorithm using convolutional features from intermediate layer of deep learning
Multimedia tools and applications, 2020Yuantao Chen +8 more
semanticscholar +1 more source