IEEE Organizations related to Image Annotation

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Conferences related to Image Annotation

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Multimedia and Expo (ICME)

Multimedia technologies, systems and applications for both research and development of communications, circuits and systems, computer, and signal processing communities.

  • 2019 IEEE International Conference on Multimedia and Expo (ICME)

    speech, audio, image, video, text and new sensor signal processingsignal processing for media integration3D imaging, visualization and animationvirtual reality and augmented realitymulti-modal multimedia computing systems and human-machine interactionmultimedia communications and networkingmedia content analysis and searchmultimedia quality assessmentmultimedia security and content protectionmultimedia applications and servicesmultimedia standards and related issues

  • 2018 IEEE International Conference on Multimedia and Expo (ICME)

    The IEEE International Conference on Multimedia & Expo (ICME) has been the flagship multimedia conference sponsored by four IEEE societies since 2000. It serves as a forum to promote the exchange of the latest advances in multimedia technologies, systems, and applications from both the research and development perspectives of the circuits and systems, communications, computer, and signal processing communities. ICME also features an Exposition of multimedia products and prototypes.

  • 2017 IEEE International Conference on Multimedia and Expo (ICME)

    Topics of interest include, but are not limited to: – Speech, audio, image, video, text and new sensor signal processing – Signal processing for media integration – 3D visualization and animation – 3D imaging and 3DTV – Virtual reality and augmented reality – Multi-modal multimedia computing systems and human-machine interaction – Multimedia communications and networking – Media content analysis – Multimedia quality assessment – Multimedia security and content protection – Multimedia databases and digital libraries – Multimedia applications and services – Multimedia standards and related issues

  • 2016 IEEE International Conference on Multimedia and Expo (ICME)

    Topics of interest include, but are not limited to:- Speech, audio, image, video, text and new sensor signal processing- Signal processing for media integration- 3D visualization and animation- 3D imaging and 3DTV- Virtual reality and augmented reality- Multi-modal multimedia computing systems and human-machine interaction- Multimedia communications and networking- Media content analysis- Multimedia quality assessment- Multimedia security and content protection- Multimedia databases and digital libraries- Multimedia applications and services- Multimedia standards and related issues

  • 2015 IEEE International Conference on Multimedia and Expo (ICME)

    With around 1000 submissions and 500 participants each year, the IEEE International Conference on Multimedia & Expo (ICME) has been the flagship multimedia conference sponsored by four IEEE societies since 2000. It serves as a forum to promote the exchange of the latest advances in multimedia technologies, systems, and applications from both the research and development perspectives of the circuits and systems, communications, computer, and signal processing communities.

  • 2014 IEEE International Conference on Multimedia and Expo (ICME)

    The IEEE International Conference on Multimedia & Expo (ICME) has been the flagship multimedia conference sponsored by four IEEE societies since 2000. It serves as a forum to promote the exchange of the latest advances in multimedia technologies, systems, and applications. In 2014, an Exposition of multimedia products, prototypes and animations will be held in conjunction with the conference.Topics of interest include, but are not limited to:

  • 2013 IEEE International Conference on Multimedia and Expo (ICME)

    To promote the exchange of the latest advances in multimedia technologies, systems, and applications from both the research and development perspectives of the circuits and systems, communications, computer, and signal processing communities.

  • 2012 IEEE International Conference on Multimedia and Expo (ICME)

    IEEE International Conference on Multimedia & Expo (ICME) has been the flagship multimedia conference sponsored by four IEEE Societies. It exchanges the latest advances in multimedia technologies, systems, and applications from both the research and development perspectives of the circuits and systems, communications, computer, and signal processing communities.

  • 2011 IEEE International Conference on Multimedia and Expo (ICME)

    Speech, audio, image, video, text processing Signal processing for media integration 3D visualization, animation and virtual reality Multi-modal multimedia computing systems and human-machine interaction Multimedia communications and networking Multimedia security and privacy Multimedia databases and digital libraries Multimedia applications and services Media content analysis and search Hardware and software for multimedia systems Multimedia standards and related issues Multimedia qu

  • 2010 IEEE International Conference on Multimedia and Expo (ICME)

    A flagship multimedia conference sponsored by four IEEE societies, ICME serves as a forum to promote the exchange of the latest advances in multimedia technologies, systems, and applications from both the research and development perspectives of the circuits and systems, communications, computer, and signal processing communities.

  • 2009 IEEE International Conference on Multimedia and Expo (ICME)

    IEEE International Conference on Multimedia & Expo is a major annual international conference with the objective of bringing together researchers, developers, and practitioners from academia and industry working in all areas of multimedia. ICME serves as a forum for the dissemination of state-of-the-art research, development, and implementations of multimedia systems, technologies and applications.

  • 2008 IEEE International Conference on Multimedia and Expo (ICME)

    IEEE International Conference on Multimedia & Expo is a major annual international conference with the objective of bringing together researchers, developers, and practitioners from academia and industry working in all areas of multimedia. ICME serves as a forum for the dissemination of state-of-the-art research, development, and implementations of multimedia systems, technologies and applications.

  • 2007 IEEE International Conference on Multimedia and Expo (ICME)

  • 2006 IEEE International Conference on Multimedia and Expo (ICME)

  • 2005 IEEE International Conference on Multimedia and Expo (ICME)

  • 2004 IEEE International Conference on Multimedia and Expo (ICME)

  • 2003 IEEE International Conference on Multimedia and Expo (ICME)

  • 2002 IEEE International Conference on Multimedia and Expo (ICME)

  • 2001 IEEE International Conference on Multimedia and Expo (ICME)

  • 2000 IEEE International Conference on Multimedia and Expo (ICME)


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


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Periodicals related to Image Annotation

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Most published Xplore authors for Image Annotation

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Xplore Articles related to Image Annotation

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Context Aware Image Annotation in Active Learning with Batch Mode

2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), 2019

Bags are not isolated in the Multiple-Instance Active Learning process, especially for image as bag, because each picture has its inherent background or metainformation, such as its taken time, taken place, the topic, and they have possible associations. With context associations, we can build the annotation tool providing more interactively user experience and thus increase the annotation efficiency. In this ...


Video annotation tools: A Review

2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018

Due to the advancements of Machine learning and vast usage of multimedia data, the image and video annotation has become quite popular now. In the area of image annotation, the researchers and specially Microsoft research lab have achieved nearly 98% accuracy. But same is not true for the video annotation. This paper presents a review of the state of the ...


Deep Textual Searching for Visual Semantics of Personal Photo Collections with a Hybrid Similarity Measure

2017 International Symposium on Computer Science and Intelligent Controls (ISCSIC), 2017

In recent years, personal photos on the internet have become important parts of people's lives. There is much automatic application software to search for photos, but searching still suffers from problems of semantic accuracy. Research has been conducted to satisfy user demands for a semantic model using a set of features or keyword annotation techniques. Keywords in photos give the ...


Semi-automatic image and video annotation system for generating ground truth information

2018 International Conference on Information Networking (ICOIN), 2018

Recently, techniques for automatically interpreting images or videos through machine learning based on big data have been actively studied. In this paper, we propose a semiautomatic image and video annotation system to generate ground truth information, which is essential information for machine learning of images or videos. Unlike the conventional methods for generating simple ground truth information manually, the proposed ...


Multi label learning and multi feature extraction for automatic image annotation

2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA), 2017

Recently, various multimedia technologies has been developed, which increase the collection of digital images. In daily life, popularity of digital camera and social media is also increased which is resulted in huge digital data sharing. Within such large amount of image data, specific image searching is very difficult. To make ease of searching, dictionary learning becomes popular solution. The feature ...


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Educational Resources on Image Annotation

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IEEE-USA E-Books

  • Context Aware Image Annotation in Active Learning with Batch Mode

    Bags are not isolated in the Multiple-Instance Active Learning process, especially for image as bag, because each picture has its inherent background or metainformation, such as its taken time, taken place, the topic, and they have possible associations. With context associations, we can build the annotation tool providing more interactively user experience and thus increase the annotation efficiency. In this paper, we propose a context aware images annotation framework that selects the images that are context related to query in the multiple-instance active learning with batch mode. Experiments show that it takes less time for annotation with the proposed framework compared to traditional ones, and improve the labeling efficiency.

  • Video annotation tools: A Review

    Due to the advancements of Machine learning and vast usage of multimedia data, the image and video annotation has become quite popular now. In the area of image annotation, the researchers and specially Microsoft research lab have achieved nearly 98% accuracy. But same is not true for the video annotation. This paper presents a review of the state of the art tools being used for video annotation.

  • Deep Textual Searching for Visual Semantics of Personal Photo Collections with a Hybrid Similarity Measure

    In recent years, personal photos on the internet have become important parts of people's lives. There is much automatic application software to search for photos, but searching still suffers from problems of semantic accuracy. Research has been conducted to satisfy user demands for a semantic model using a set of features or keyword annotation techniques. Keywords in photos give the best evidence to identify what photos are about. However, it does not always relate to the actual meaning of photos.For this reason, we propose a textual description with a hierarchical concept and comparison of the feature set with a hybrid similarity measure. The experimental results indicate that our proposed approach offers significant performance improvements in the interpretation of semantic meanings with a maximum success rate of 80.4%.

  • Semi-automatic image and video annotation system for generating ground truth information

    Recently, techniques for automatically interpreting images or videos through machine learning based on big data have been actively studied. In this paper, we propose a semiautomatic image and video annotation system to generate ground truth information, which is essential information for machine learning of images or videos. Unlike the conventional methods for generating simple ground truth information manually, the proposed system not only provides various ground truth information such as object information, motion information, and event information, but also uses a semi-automatic image and video annotation method for fast generation of ground truth information. The ground truth information generated by the proposed system is stored in the metadata database as a form of XML. The implementation results show that the proposed system provides not only fast ground truth annotation, but also more various ground truth information compared to the existing methods.

  • Multi label learning and multi feature extraction for automatic image annotation

    Recently, various multimedia technologies has been developed, which increase the collection of digital images. In daily life, popularity of digital camera and social media is also increased which is resulted in huge digital data sharing. Within such large amount of image data, specific image searching is very difficult. To make ease of searching, dictionary learning becomes popular solution. The feature based image annotation is the new area for image searching. In this image annotation task, some human keywords are assigned to the images, so that searching becomes easy. In this paper, we present a multi- label learning and multi keyword extraction for automatic image annotation. This framework is worked in two phases named as training and testing phase. In training phase, we build the classifier with the help of extracted features, mapping of tags and features and dictionary learning. This classifier is used to identify the labels for testing image. For classification we have used C4.5 classifier and prove that the accuracy and efficiency is better than naïve byes classifier. The performance of system is tested on IAPR TC12 dataset. Experimental results prove that the multiple label and multiple features extraction improves the efficiency of image annotation framework.

  • Computing Crowd Consensus with Partial Agreement

    Crowdsourcing has been widely established as a means to enable human computation at large-scale, in particular for tasks that require manual labelling of large sets of data items. Answers obtained from heterogeneous crowd workers are aggregated to obtain a robust result. In this paper, we consider partial-agreement tasks that are common in many applications such as image tagging and document annotation, where items are assigned sets of labels. Going beyond the state-of-the-art, we propose a novel Bayesian nonparametric model to aggregate the partial-agreement answers in a generic way. This model enables us to compute the consensus of partially-sound and partially-complete worker answers, while taking into account mutual relations in labels and different answer sets. An evaluation of our method using real- world datasets reveals that it consistently outperforms the state-of-the-art in terms of precision, recall, and scalability.

  • Semi-automatic annotation of distorted image based on neighborhood rough set

    In the field of image distortion, the difficulty of image annotation is mainly reflected in three points:(1)The appraiser's evaluation annotation is inconsistent; (2)The boundary definition of the image distortion type is fuzzy;(3)The environment atmosphere of the tagging work is complex. Three kinds of difficulties are often caused by the ambiguity in the distortion of image annotation results. As an effective solution to ambiguity and uncertainty. In this paper, a semi-automatic method based on neighborhood rough sets is proposed for distorted images. The aim of this paper is to improve the accuracy of annotation by constructing a global rough set model. Specifically, under the constraint of defined annotation rules. The sample is annotated by manual annotation, and the approximate neighborhood of the sample is constructed. Then according to the approximate neighborhood coordinates, calculate the coordinates in the neighborhood of upper approximation and lower approximation. Finally, construct the semantic association between the annotation words and the images, so as to classify the images. The experimental results show that the method has achieved effective results in image distortion classification.

  • Building Detection and Segmentation Using a CNN with Automatically Generated Training Data

    Significantly outperforming traditional machine learning methods, deep convolutional neural networks have gained increasing popularity in the application of image classification and segmentation. Nevertheless, deep learning-based methods usually require a large amount of training data, which is quite labor-intensive and time-demanding. To deal with the problem in generating training data, we propose in this paper a novel approach to generate image annotations by transferring labels from aerial images to UAV images and refine the annotations using a densely connected CRF model with an embedded naive Bayes classifier. The generated annotations not only present correct semantic labels, but also preserve accurate class boundaries. To validate the utility of these automatic annotations, we deploy them as training data for pixel-wise image segmentation and compare the results with the segmentation using manual annotations. Experiment results demonstrate that the automatic annotations can achieve comparable segmentation accuracy as the manual annotations.

  • Co-Cleansing of Image and Text Dataset by Automatic Image Annotation and Proper Noun Analysis

    There are many types of relations between images and texts in native multimedia data on the Web describing, for instance, general subjects, events, persons, etc. We propose a novel automatic multimedia data cleansing method that selects pairs of an image and a piece of text (paragraph or sentence) describing only general subjects. The selected dataset describing the general subject is thus available to be used for annotation learning. Experiments conducted on Wikipedia data confirmed that our method can automatically select image and text pairs describing general subjects.

  • PESSN: Precision Enhancement Method for Semantic Segmentation Network

    Semantic segmentation to understand an image at pixel level is an important problem in the computer vision. In the traditional object detection, each object in an image is detected at its minimum bounding rectangle level, but, in the semantic segmentation, it is detected at pixel level and thus the segmentation result is more flexible and meaningful. However, the characteristics of the semantic segmentation network might make over- segmentation with a few pixels misunderstood and result in the low precision rate. In this paper, we propose a method to enhance the precision rate of the semantic segmentation network. In order to address the over-segmentation, we define confidence-based and semantic-correlation-based outliers. Confidence- based outlier is defined by the confidence value, weighted by the number of segment's pixels, of the semantic segmentation network and semantic- correlation-based outlier is defined by the distance in the Word2Vec space. If a pixel is determined as not only confidence-based but also semantic- correlation-based outlier, the pixel is pruned from the segmentation result. We evaluate the proposed method with the images of COCO dataset and show the f-score, as well as the precision rate, of the semantic segmentation is significantly improved.



Standards related to Image Annotation

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Jobs related to Image Annotation

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