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Automatic image annotation refinement
2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2016Automatic image annotation methods automatically assign labels to images in order to facilitate tasks such as image retrieval, search, organizing and management. Incorrect labels may negatively influence the search results so image annotation should be as accurate as possible.
Miran Pobar, Marina Ivasic-Kos
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Semi-Automatic Semantic Annotation of Images
Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007Detailed, consistent semantic annotation of large collections of multimedia data is difficult and time-consuming. In domains such as eScience, digital curation and industrial monitoring, finegrained high-quality labeling of regions enables advanced semantic querying, analysis and aggregation and supports collaborative research.
Suzanne Little +2 more
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Geo-based automatic image annotation
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, 2012A huge number of user-tagged images are daily uploaded to the web. Recently, a growing number of those images are also geotagged. These provide new opportunities for solutions to automatically tag images so that efficient image management and retrieval can be achieved. In this paper an automatic image annotation approach is proposed.
Hatem Mousselly Sergieh +5 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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Exploiting ontologies for automatic image annotation
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, 2005Automatic image annotation is the task of automatically assigning words to an image that describe the content of the image. Machine learning approaches have been explored to model the association between words and images from an annotated set of images and generate annotations for a test image.
Munirathnam Srikanth +3 more
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Hierarchical classification for automatic image annotation
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007In this paper, a hierarchical classification framework has been proposed for bridging the semantic gap effectively and achieving multi-level image annotation automatically. First, the semantic gap between the low-level computable visual features and users' real information needs is partitioned into four smaller gaps, and multiple approachesallare ...
Jianping Fan 0001, Yuli Gao, Hangzai Luo
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Automatic image annotation with continuous PLSA
2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we firstly extend probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding Expectation-Maximization (EM) algorithm is derived to determine the model parameters.
Zhixin Li 0001 +3 more
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A hybrid automatic image annotation approach
Multimedia Tools and Applications, 2018Automated image annotation (AIA) is an important issue in computer vision and pattern recognition, and plays an extremely important role in retrieving large-scale images. In many image annotation approaches, different regions of the image are processed equally, which is inconsistent with the mechanism by which humans understand images.
Cong Jin, Qing-Mei Sun, Shu-Wei Jin
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Automatic Image Annotation by Mining the Web
2006Automatic image annotation has been becoming an attractive research subject. Most current image annotation methods are based on training techniques. The major weaknesses of such solutions include limited annotation vocabulary and labor-intensive involvement.
Zhiguo Gong, Qian Liu, Jingbai Zhang
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Neural ranking for automatic image annotation
Multimedia Tools and Applications, 2018Automatic image annotation aims to predict labels for images according to their semantic contents and has become a research focus in computer vision, as it helps people to edit, retrieve and understand large image collections. In the last decades, researchers have proposed many approaches to solve this task and achieved remarkable performance on ...
Weifeng Zhang 0002 +2 more
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