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Semi-automatic Semantic Annotation of Images Using Machine Learning Techniques [chapter]

Oge Marques, Nitish Barman
2003 Lecture Notes in Computer Science  
visual levels -is used to speed up the annotation of subsequent images within the same domain (ontology) as well as to improve future query and retrieval of annotated images.  ...  Our key contribution is the use of machine learning algorithms for user-assisted, semi-automatic image annotation, in such a way that the knowledge of previously annotated images -both at metadata and  ...  The authors want to thank Dragutin Petkovic for his excellent comments and suggestions.  ... 
doi:10.1007/978-3-540-39718-2_35 fatcat:boeiiztfmrf6vickp4glrk5cga

A Context Centric Approach for Semantic Image Annotation and Retrieval

Najeeb Elahi, Randi Karlsen, Sigmund Akselsen
2009 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns  
In this preliminary research, we discuss techniques to improve the quality of image retrieval and image management with the help of context information over the web.  ...  Our hypothesis is that leveraging the semantic annotated contextual metadata of the image would yield the relevant search results and facilitate building a consistent, unambiguous image knowledge base.  ...  The most common approaches used for image retrieval are Text-Based Image Retrieval (TBIR) and Content-Based Image Retrieval (CBIR).  ... 
doi:10.1109/computationworld.2009.30 fatcat:7wjpfwfrxjb3nhu65kuqovtb6i

Visual features with semantic combination using Bayesian network for a more effective image retrieval

Sabine Barrat, Salvatore Tabbone
2008 Pattern Recognition (ICPR), Proceedings of the International Conference on  
Results of visual-textual retrieval associated to a relevance feedback process, reported on a database of images collected from the Web, partially and manually annotated, show an improvement of about 44.5%  ...  We present and evaluate a new method which improves the effectiveness of content-based image retrieval, by integrating semantic concepts extracted from text.  ...  We have done our experiments on a partially annotated Web image database.  ... 
doi:10.1109/icpr.2008.4761468 dblp:conf/icpr/BarratT08 fatcat:k7lejb722vgxdo7cv6wkuaayjm

Celebrity Face Naming based on Relationships and Knowledge using Caption-Based Supervision

Jyoti H. Jadhav, Pankaj Agarkar
2017 IARJSET  
Relationship is the appearance of faces under different context and their visual similarities. The knowledge includes Web images weakly tagged with celebrity names and the celebrity social networks.  ...  Mining weakly labeled web facial images on the internet has emerged as a promising paradigm towards auto face annotation.  ...  Multiple FR engines available in online social networks (OSN"s) are used for effective FR.  ... 
doi:10.17148/iarjset/nciarcse.2017.18 fatcat:cx2ocrkpvbfwrk3urdryfuksce

Classification and Automatic Annotation Extension of Images Using Bayesian Network [chapter]

Sabine Barrat, Salvatore Tabbone
2008 Lecture Notes in Computer Science  
Results of visualtextual classification, reported on a database of images collected from the Web, partially and manually annotated, show an improvement by 32.3% in terms of recognition rate against only  ...  In this paper we present and evaluate a new method which improves the effectiveness of content-based image classification, by integrating semantic concepts extracted from text, and by automatically extending  ...  Finally, automatic image annotation can be used in image retrieval systems to organize and locate images of interest from a database, or to perform visualtextual classification.  ... 
doi:10.1007/978-3-540-89689-0_97 fatcat:mzrq6dvvanh7bmnwdffnucrwpi

Building and Querying RDF/OWL Database of Semantically Annotated Nuclear Medicine Images

Kyung Hoon Hwang, Haejun Lee, Geon Koh, Debra Willrett, Daniel L. Rubin
2016 Journal of digital imaging  
We constructed a semantically structured database of nuclear medicine images using the Annotation and Image Markup (AIM) format and evaluated the ability the AIM annotations to improve image search.  ...  Further study using a larger data set and the implementation of an inference engine may improve query results for more complex queries.  ...  Further studies using larger data sets and including an implementation of inference may improve image query performance.  ... 
doi:10.1007/s10278-016-9916-7 pmid:27785632 pmcid:PMC5267605 fatcat:o5ur4anubbfoxjecyhabg5kuz4

Knowledge Resource Development for Identifying Matching Image Descriptions

Alicia Sagae, Scott E. Fahlman
2013 Proceedings of the International Conference on Knowledge Engineering and Ontology Development  
knowledge resources contribute to the performance of many current systems for textual inference tasks (QA, textual entailment, summarization, retrieval, and others).  ...  This paper describes the incremental, task-driven development of an ontology that provides features to a system that retrieves images based on their textual descriptions.  ...  As a result, MIRFLICKR has been used for image annotation and retrieval by visual example, but is not sufficient for testing retrieval by phrasal description.  ... 
doi:10.5220/0004550601000108 dblp:conf/ic3k/SagaeF13 fatcat:22cuezse4fdkvfisn2ztfuvc4m

Emerging Trends in Reducing Semantic Gap towards Multimedia Access: A Comprehensive Survey

Aijazahamed Qazi, R. H. Goudar
2016 Indian Journal of Science and Technology  
Application/Improvement: Use of Description logics increases the efficiency of semantic retrieval.  ...  Semantic web is combined with statistical and machine learning techniques to increase the efficiency of an information retrieval system.  ...  The Geospatial information is retrieved by using fuzzy logic.. 2 provide an overview of computational system that combines annotation with image classification.  ... 
doi:10.17485/ijst/2016/v9i30/99072 fatcat:asnamx3urveabjyritsri3guuy

Semantic Concept Co-Occurrence Patterns for Image Annotation and Retrieval

Linan Feng, Bir Bhanu
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence  
ACKNOWLEDGMENTS This material is based upon work supported by the National Science Foundation under Grant No. 0905671 and 1552454.  ...  assist in image annotation and retrieval.  ...  Third, object bank is used to address the scene classification and object recognition tasks while our concept signature is used for image annotation and semantic image retrieval.  ... 
doi:10.1109/tpami.2015.2469281 pmid:26959678 fatcat:enu2lsrmzfgsfp4vvf5hj3d27y

Semantic image annotation using convolutional neural network and wordnet ontology

Jaison Saji Chacko, Tulasi B
2018 International Journal of Engineering & Technology  
Accurate annotation is critical for efficient image search and retrieval.  ...  Semantic image annotation refers to adding meaningful meta-data to an image which can be used to infer additional knowledge from an image.  ...  We believe that this is the first attempt to improve semantic annotation of images using deep learning and WordNet ontology by creating abstractions using LCH.  ... 
doi:10.14419/ijet.v7i2.27.9886 fatcat:7ow6ocw22ng5xiydntzwnftvay

Photo annotation on a camera phone

Anita Wilhelm, Yuri Takhteyev, Risto Sarvas, Nancy Van House, Marc Davis
2004 Extended abstracts of the 2004 conference on Human factors and computing systems - CHI '04  
In this paper we present usability issues encountered in using a camera phone as an image annotation device immediately after image capture and users' responses to use of such a system.  ...  The system uses camera phones with a lightweight client application and a server to store the images and metadata and assists the user in annotation on the camera phone by providing guesses about the content  ...  As networks improve, our problems with network latency and unreliability will be reduced.  ... 
doi:10.1145/985921.986075 dblp:conf/chi/WilhelmTSHD04 fatcat:as52ic233bbotifncf5xhnogvm

A generic framework for ontology-based information retrieval and image retrieval in web data

V. Vijayarajan, M. Dinakaran, Priyam Tejaswin, Mayank Lohani
2016 Human-Centric Computing and Information Sciences  
Additionally, image search engines, such as Google Images, use content-based image information extraction and retrieval of web pages against the user query.  ...  First, how to combine the use of domain ontology and semantics to improve information retrieval and user experience?  ...  In traditional text-based image annotations, the images are manually annotated by humans, and the annotations are used as an index for image retrieval [13, 14] .  ... 
doi:10.1186/s13673-016-0074-1 fatcat:oxb7bivxlrexra5274o6zyteiq

A Survey On Semantic Image Retrieval For Bigdata

Ms.N.N. Deepika, Dr. R. Madhumitha
2017 International Journal Of Engineering And Computer Science  
In Semantic based image retrieval, the weight adjustment scheme is used to give the high priority for the contents which are semantically more related.  ...  Every day, millions of images are being generated, in that semantic Image retrieval is the most complex process in the real time scenario where the similarity finding would be more difficult in case of  ...  It is then introduced and described an Information Retrieval algorithm using an Object-Fuzzy Concept Network (O-FCN). III.  ... 
doi:10.18535/ijecs/v6i3.21 fatcat:worc74lj6vas7i2dh4vbrctfo4

Recent Trends on Content Based Image Retrieval System- An Overview

Rajsheel Sharma, Prof. Ratnesh Dubey, Dr.Vineet Richariya
2016 IOSR Journal of Computer Engineering  
The Content-Based Image Retrieval (CBIR) techniques comprise methodologies intended to retrieve self-content descriptors over the image data set being studied according to the type of the image.  ...  The main purpose of CBIR consists in classifying images avoiding the use of manual labels related to understanding of the image by the human being vision.  ...  .  Fast retrieval.  Web image search (surrounding text).  IV.  ... 
doi:10.9790/0661-1804064853 fatcat:ulymifg47bcq7iwgtqcwbup4zm

Self-Supervised Learning from Web Data for Multimodal Retrieval [article]

Raul Gomez, Lluis Gomez, Jaume Gibert, Dimosthenis Karatzas
2019 arXiv   pre-print
Self-Supervised learning from multimodal image and text data allows deep neural networks to learn powerful features with no need of human annotated data.  ...  We show that the embeddings learnt with Web and Social Media data have competitive performances over supervised methods in the text based image retrieval task, and we clearly outperform state of the art  ...  Industrials program from the Generalitat de Catalunya, the Spanish project TIN2017-89779-P, the H2020 Marie Skłodowska-Curie actions of the European Union, grant agreement No 712949 (TECNIOspring PLUS), and  ... 
arXiv:1901.02004v1 fatcat:wpibqwyf2rax7ltrahjnw6vvxy
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