Conferences related to Image Recognition

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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 Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


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)


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


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Periodicals related to Image Recognition

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


Geoscience and Remote Sensing, IEEE Transactions on

Theory, concepts, and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.


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Most published Xplore authors for Image Recognition

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Xplore Articles related to Image Recognition

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Image Recognition Based on Optical Wavelet and Support Vector Machine

2011 International Conference on Information Management, Innovation Management and Industrial Engineering, 2011

Image recognition belongs to the nonlinear classification problem, which has a certain difficulty in the process of image recognition. Image recognition based on optical wavelet and support vector machine is proposed in the paper. Optical wavelet is used to extract the features of images and support vector machine is used to create the image recognition model by utilizing the features. ...


Students course “introduction to industrial image recognition”

2016 International Conference and Exposition on Electrical and Power Engineering (EPE), 2016

In part I of this paper a brief overview about state-of-the-art industrial image processing is given. Part II shows how an introduction of this technology can be taught to newcomers in the field, how problems can be solved using image recognition and processing systems and how this can be achieved with good success within very short teaching time by means ...


A Study on Hybrid Approaches in Image Recognition System

2007 IEEE Intelligent Vehicles Symposium, 2007

Hybrid approaches have been applied widely in image recognition system to adapt the increasing requirement of real-time and high accuracy and there are a lot of successful hybrid image recognition algorithms. To use hybrid approaches more effectively, some basic research about it is very necessary. This paper analyzes current typical hybrid samples, then presents basic hybrid image recognition patterns and ...


Application of video image recognition technology in substation equipments monitoring

2011 International Conference on Electrical and Control Engineering, 2011

There are lots of electric equipments in the substation, whether they work properly or not is always related to the working security and stability of substation. Therefore, applying video image recognition technology in substation equipments monitoring is a method which can protect and maintain the equipments effectively. This paper introduces the application of video image recognition technology briefly in current ...


Development of RT-Middleware for Image Recognition Module

2006 SICE-ICASE International Joint Conference, 2006

We have developed "image recognition device and module" in "development project for a common basis of next-generation robots" that is the consignment business of new energy and industrial technology development organization (NEDO). The purpose of this project is to develop image recognition module that is little hardware-scale, little power-consumption, useful and high- performance. The authors implemented the RT-middleware on embedded ...


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Educational Resources on Image Recognition

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IEEE-USA E-Books

  • Image Recognition Based on Optical Wavelet and Support Vector Machine

    Image recognition belongs to the nonlinear classification problem, which has a certain difficulty in the process of image recognition. Image recognition based on optical wavelet and support vector machine is proposed in the paper. Optical wavelet is used to extract the features of images and support vector machine is used to create the image recognition model by utilizing the features. In the experiments, 80 images with 9 classes are used to study the effectiveness of the proposed OWSVM method. Image recognition accuracy of the proposed OWSVM method is 96.25 and image recognition accuracy of OWBPNN is 88.75.The experimental results show that image recognition accuracy of the proposed OWSVM method is better than that of OWBPNN.

  • Students course “introduction to industrial image recognition”

    In part I of this paper a brief overview about state-of-the-art industrial image processing is given. Part II shows how an introduction of this technology can be taught to newcomers in the field, how problems can be solved using image recognition and processing systems and how this can be achieved with good success within very short teaching time by means of a step-by-step example.

  • A Study on Hybrid Approaches in Image Recognition System

    Hybrid approaches have been applied widely in image recognition system to adapt the increasing requirement of real-time and high accuracy and there are a lot of successful hybrid image recognition algorithms. To use hybrid approaches more effectively, some basic research about it is very necessary. This paper analyzes current typical hybrid samples, then presents basic hybrid image recognition patterns and evaluates their performance about real-time, accuracy, robustness, expandability and flexibility. At last a developing hybrid image recognition system would be introduced as a sample.

  • Application of video image recognition technology in substation equipments monitoring

    There are lots of electric equipments in the substation, whether they work properly or not is always related to the working security and stability of substation. Therefore, applying video image recognition technology in substation equipments monitoring is a method which can protect and maintain the equipments effectively. This paper introduces the application of video image recognition technology briefly in current situation and proposes different schemes of image preprocessing and image recognition based on different situations, which can solve the problems of meter display information recognition, switch position recognition and working states recognition of Transformer-fan-set of substation. The results show that video image recognition applied in substation equipments monitoring has broad prospects.

  • Development of RT-Middleware for Image Recognition Module

    We have developed "image recognition device and module" in "development project for a common basis of next-generation robots" that is the consignment business of new energy and industrial technology development organization (NEDO). The purpose of this project is to develop image recognition module that is little hardware-scale, little power-consumption, useful and high- performance. The authors implemented the RT-middleware on embedded processor DSP (digital signal processor) for image recognition module, for improve the development efficiency of component, and to offer the easy-to-use interfaces. In this paper, we introduce our project, concept of RT-middleware, and mechanism of RT-middleware for image recognition module that we have developed

  • SOC for car navigation system with a 55.3GOPS image recognition engine

    This paper introduces the system on a chip (SOC) equipped with dual RISC processors, an image recognition engine operating with up to 55.3 GOPS, multiple accelerators and peripherals for car navigation systems. The SoC has high performance with respect to image recognition applications which are installed in advanced vehicles as well as navigation function such as graphics operating at the same time. Furthermore we have developed the SoC in order to meet automotive specifications including cost and size. We report practical application which is for the pedestrian detection to demonstrate our SoC capability. We accelerate the application with combination of the RISC processor and image recognition engine.

  • Content-based image recognition technique using area moments

    We propose an automatic moment-based image recognition technique in this paper. The problem to be solved consists of classifying the images from a set, using the content similarity. In the feature extraction stage, we compute a set of feature vectors using area moments. An automatic unsupervised feature vector classification approach is proposed next. It uses a hierarchical agglomerative clustering algorithm, the optimal number of clusters being determined using validation indexes.

  • ICME 2016 Image Recognition Grand Challenge

    This paper summarizes the MSR Image Recognition Challenge (IRC) running with ICME 2016 Grand Challenges. Since 2013, Microsoft Research has hosted a series of IRCs to motivate the academic and industrial community to solve real-world large-scale image retrieval and recognition problems. This IRC in ICME 2016 continually leveraged the Clickture dataset [1], a large-scale real-world image click data consisting of 40M web images, and a derived subset of 95K dog-related images for the challenge of dog breed recognition. To conduct fair and efficient evaluation, and make the recognition result more reproducible and accessible, the contest runs on an open platform, Prajna Hub, which can help convert a research algorithm into an online service with minimal effort of just a few hours. As part of the ICME 2016 Grand Challenges, more than 30 teams participated this year's MSR IRC and 10 teams successfully finished the task. More details of data, system, metrics, process, and result are described in this paper.

  • Research on Image Recognition of Insulators Based on YOLO Algorithm

    Insulators are important components of power transmission and transformation equipment in power systems. Insulator identification is a basis work for evaluation of insulation status of insulators in computer vision. With the recent development of big data and cloud computing technologies, terminal-to- terminal picture recognition was accomplished based on deep learning algorithms, making it possible to apply insulator image recognition in power systems. This paper firstly introduced the research background of deep learning: the recent YOLO (You Only Look Once) convolutional neural network algorithm, established insulator image databases for train and test, and preprocessed the images of training insulator images with the TensorFlow platform. With the YOLO algorithm applied, the training of the image database for 5 days was completed, and a good recognition result was achieved. Then the results were compared between the Fast R-CNN algorithm and the YOLO algorithm in identify speed and accuracy. Based on relevant paper, the accuracy of insulator image recognition is defined, and the factors that affect the accuracy of insulator image recognition are discussed: It is concluded that the accuracy of identification increases with the increase in the number of training insulators, which is the next step in the identification of insulators.

  • A Novel Method for Image Recognition Based on Polynomial Curve Fitting

    Invariant feature is desirable in image recognition and computer vision, while feature matching is limited in the distance or the relative measurement between the image and the model. In this paper, we propose a novel method for image recognition based on polynomial curve fitting. Non-redundant complex moments are derived, that are invariant to the translation, constraint scale and rotation, and complex moments below 4th order are selected as the invariant feature. With the principle of polynomial curve fitting, similarity measurement between the fitting coefficients of the non-redundant complex invariants is calculated to describe the images. Finally it is applied in real ship images and its validation is analyzed. Experimental results presented show that the described method has good stability and can be used as an effective method for image recognition.



Standards related to Image Recognition

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Jobs related to Image Recognition

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