Journal ArticleDOI
A survey of methods for image annotation
TLDR
Three image annotation approaches are reviewed: free text annotation, keyword annotation and annotation based on ontologies, which discusses the creation of keyword vocabularies for use in automated image annotation evaluation.Abstract:Â
In order to evaluate automated image annotation and object recognition algorithms, ground truth in the form of a set of images correctly annotated with text describing each image is required. In this paper, three image annotation approaches are reviewed: free text annotation, keyword annotation and annotation based on ontologies. The practical aspects of image annotation are then considered. We discuss the creation of keyword vocabularies for use in automated image annotation evaluation. As direct manual annotation of images requires much time and effort, we also review various methods to make the creation of ground truth more efficient. An overview of annotated image datasets for computer vision research is provided.read more
Citations
More filters
Multilingual information access for text, speech and images : 5th workshop of the cross-language evaluation forum, CLEF 2004, Bath, UK, September 15-17, 2004, revised selected papers
TL;DR: What Happened in CLEF 2004?.- What Happens in CLEf 2004?
Journal ArticleDOI
Bag-of-Words Representation in Image Annotation: A Review
TL;DR: This paper reviews related works based on the issues of improving and/or applying BoW for image annotation to automatically assign keywords to images, so image retrieval users are able to query images by keywords.
Patent
System and method for tagging multiple digital images
Jimmy Enström,Bo Larsson +1 more
TL;DR: In this article, a system for tagging multiple digital images includes an electronic device (10) having a display (22) for rendering digital images, and an interface (22a) in the electronic device receives an input of an area of interest within one of the rendered images.
Journal ArticleDOI
Deep learning for smart fish farming: applications, opportunities and challenges
TL;DR: In this article, the authors present a review of the current state of the art of deep learning in aquaculture, which can provide strong support for the implementation of smart fish farming, including live fish identification, species classification, behavioral analysis, feeding decision-making, size or biomass estimation, water quality prediction.
Journal ArticleDOI
Deep learning for smart fish farming: applications, opportunities and challenges
TL;DR: The purpose is to provide researchers and practitioners with a better understanding of the current state of the art of DL in aquaculture, which can provide strong support for the implementation of smart fish farming.
References
More filters
Journal ArticleDOI
A translation approach to portable ontology specifications
TL;DR: This paper describes a mechanism for defining ontologies that are portable over representation systems, basing Ontolingua itself on an ontology of domain-independent, representational idioms.
Journal ArticleDOI
Content-based image retrieval at the end of the early years
TL;DR: The working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap are discussed, as well as aspects of system engineering: databases, system architecture, and evaluation.
Journal ArticleDOI
Women, Fire, and Dangerous Things: What Categories Reveal about the Mind
Journal Article
Women, Fire, and Dangerous Things: What Categories Reveal about the Mind
TL;DR: In this article, a pengetahuan kognitif adalah tergolong bidang baru ying mengkaji pikiran atau nalar ying memperoleh pen getahuan dari bidang-bidang ilmu seperti psikologi, linguistik, antropologi and filsafat, and juga ilmu komputer.
Proceedings Article
Visual categorization with bags of keypoints
TL;DR: This bag of keypoints method is based on vector quantization of affine invariant descriptors of image patches and shows that it is simple, computationally efficient and intrinsically invariant.