Conferences related to Image edge detection

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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 18th International Conference on Industrial Informatics (INDIN)

INDIN focuses on recent developments, deployments, technology trends, and research results in Industrial Informatics-related fields from both industry and academia


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 Solid- State Circuits Conference - (ISSCC)

ISSCC is the foremost global forum for solid-state circuits and systems-on-a-chip. The Conference offers 5 days of technical papers and educational events related to integrated circuits, including analog, digital, data converters, memory, RF, communications, imagers, medical and MEMS ICs.


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Periodicals related to Image edge detection

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Reviews in

The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


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-- ...


Consumer Electronics, IEEE Transactions on

The design and manufacture of consumer electronics products, components, and related activities, particularly those used for entertainment, leisure, and educational purposes


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Most published Xplore authors for Image edge detection

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Xplore Articles related to Image edge detection

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Robust speckle reducing anisotropic diffusion

EUSAR 2012; 9th European Conference on Synthetic Aperture Radar, 2012

Speckle Filter performance strongly depends on speckle model and heterogeneity measurement. Classical single-stage speckle filters fails to retain image structures on iteration, but iteration is necessary for effective smoothing of speckle. In this paper we propose a heterogeneity measuring technique that enables to apply traditional filters iteratively. We also propose a new robust anisotropic diffusion (AD) based speckle filter (ROSRAD), ...


Cooperating Mobile Agents

Mobile Agents in Networking and Distributed Computing, None

None


Pros and Cons of Sampled Data Phase Detection

Frequency Acquisition Techniques for Phase Locked Loops, None

This chapter contains sections titled: * What are the Forms of Sampled Data Phase Detectors? * A. Ramp and Sample Analog Phase Detector * B. The RF Sampling Phase Detector * C. Edge-Triggered S-R Flip-Flop * D. Edge-Triggered Flip-Flop Ensemble * E. Sample and Hold as a Phase Detector


Integrated Vision/Force Robot System for Shelving and Retrieving of Imprecisely Placed Objects

ROBOTIK 2012; 7th German Conference on Robotics, 2012

This work suggests a new approach of robot system to shelve and retrieve imprecisely placed objects with the help of vision and force feedback according to their alphabetic/numeric codification system. A practical example of shelving and retrieving tasks is automation of libraries. Previously, automation of libraries was based on the complicated transport mechanisms and also on robotic systems without using ...


Nonlinear Unsharp Masking for the enhancement of document images

1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

A novel operator for the enhancement of the quality of document images is presented in this paper. This operator, which is a quadratic one, is based on the Unsharp Masking (UM) technique, but it is able to limit noise amplification because every pixel of the processed image depends upon a large portion of the input image; in the same time ...


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Educational Resources on Image edge detection

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IEEE.tv Videos

Low Power Image Recognition: The Challenge Continues
Noise Enhanced Information Systems: Denoising Noisy Signals with Noise
Implantable, Insertable and Wearable Micro-optical Devices for Early Detection of Cancer - Plenary Speaker, Christopher Contag - IPC 2018
Critical use cases for video capturing systems in autonomous driving applications
A Recurrent Crossbar of Memristive Nanodevices Implements Online Novelty Detection - Christopher Bennett: 2016 International Conference on Rebooting Computing
Engineering Meets Biology in Tech News
Quantization Without Fine-Tuning - Tijimen Blankevoort - LPIRC 2019
ISEC 2013 Special Gordon Donaldson Session: Remembering Gordon Donaldson - 4 of 7 - MRI at 130 Microtesla
Deep Learning & Machine Learning Inference - Ashish Sirasao - LPIRC 2019
Hamid R Tizhoosh - Fuzzy Image Processing
An FPGA-Quantum Annealer Hybrid System for Wide-Band RF Detection - IEEE Rebooting Computing 2017
P2020 Establishing Image Quality Standards for Automotive
Multi-Function VCO Chip for Materials Sensing and More - Jens Reinstaedt - RFIC Showcase 2018
One HTS Josephson Junction, An Array of Applications: Has anything come from HTS devices in the last 30 years?
Solving Sparse Representation for Image Classification using Quantum D-Wave 2X Machine - IEEE Rebooting Computing 2017
Zohara Cohen AMA EMBS Individualized Health
Build Your Career: IEEE Metro Area Workshops
ISEC 2013 Special Gordon Donaldson Session: Remembering Gordon Donaldson - 5 of 7 - SQUID Instrumentation for Early Cancer Diagnostics
From Edge To Core: Memory-Driven Hardware and Software Co-Design - IEEE Rebooting Computing Industry Summit 2017
Edge Computing for 5G, Use Cases and Evolution - Srinivasan Ramanujam - India Mobile Congress, 2018

IEEE-USA E-Books

  • Robust speckle reducing anisotropic diffusion

    Speckle Filter performance strongly depends on speckle model and heterogeneity measurement. Classical single-stage speckle filters fails to retain image structures on iteration, but iteration is necessary for effective smoothing of speckle. In this paper we propose a heterogeneity measuring technique that enables to apply traditional filters iteratively. We also propose a new robust anisotropic diffusion (AD) based speckle filter (ROSRAD), that shown to perform better than the existing speckle reducing AD filters like SRAD and DPAD. Performance of ROSRAD is tested on simulated and real SAR images and compared with other AD filters.

  • Cooperating Mobile Agents

    None

  • Pros and Cons of Sampled Data Phase Detection

    This chapter contains sections titled: * What are the Forms of Sampled Data Phase Detectors? * A. Ramp and Sample Analog Phase Detector * B. The RF Sampling Phase Detector * C. Edge-Triggered S-R Flip-Flop * D. Edge-Triggered Flip-Flop Ensemble * E. Sample and Hold as a Phase Detector

  • Integrated Vision/Force Robot System for Shelving and Retrieving of Imprecisely Placed Objects

    This work suggests a new approach of robot system to shelve and retrieve imprecisely placed objects with the help of vision and force feedback according to their alphabetic/numeric codification system. A practical example of shelving and retrieving tasks is automation of libraries. Previously, automation of libraries was based on the complicated transport mechanisms and also on robotic systems without using the vision or force/torque system. Hence, the system will bring additional drawbacks which can be eliminated by using vision system; these drawbacks cause the waste of energy and need more maintenance. In this work the proposed vision system detects objects, position/orientation, characterizes and classifies the objects, identify the codes assigned to objects (SIFT features), and provides automatically decisions which define the art of the control (when vision or force feedback should be used). The proposed control can perform position control only or combination of force-vision control depending on the conditions of the task and the environment.

  • Nonlinear Unsharp Masking for the enhancement of document images

    A novel operator for the enhancement of the quality of document images is presented in this paper. This operator, which is a quadratic one, is based on the Unsharp Masking (UM) technique, but it is able to limit noise amplification because every pixel of the processed image depends upon a large portion of the input image; in the same time a good response on details is obtained. A formal description of the operator's response to noise is also presented.

  • A rational N× image interpolator

    In this paper we present an innovative interpolator which performs high quality N× interpolation on both synthetic and real world images. Its structure, which is based on a rational operator, provides edge sensitive data interpolation, so that sharp and artifact free images are obtained.

  • Non causal adaptive quadratic filters for image filtering and contrast enhancement

    In image contrast enhancement [2, 4, 5], quadratic and more generally polynomial filters are a very popular class of nonlinear filters. These filters exhibit good performances in terms of visual quality, but present some drawbacks such as the elimination of usefull information when using a fixed filter. In this paper we propose a new family of adaptive quadratic filters, where a weighted filter mask is adaptively determined according to the minimization of a prediction error. This filter is then used to enhance locally the image contrast. The results we proposed point out the improvement provided by these new filters in comparison with recent approaches [4, 2].

  • Facial feature extraction using genetic algorithms

    Face models are used in such applications as videotelephone, graphic animation and automatic answering devices. Extraction and localization of facial features is the first step in constructing and adapting face models. Typical facial features are the eyes, the lips, the chin contour, and the nostrils. In this work, novel deformatile templates in combination with genetic algorithms are used to capture eyes and lips contours.

  • 2-D adaptive piecewise-linear filter for image enhancement

    A two-dimensional adaptive nonlinear filter, called 2-D FIR-PWL filter is introduced for noise cancellation from images. It is based on the cascade of a linear FIR filter and a piecewise-linear interpolating function. Experimental results show a very good behaviour of the filter, which outperforms in many application examples the Sigma filter both in terms of visual quality and numerical results.

  • A morphological algorithm for photomosaicking

    We define a morphological algorithm to combine two overlapping images into a single one by a process named photomosaicking. By means of a very powerful morphological operation, namely, the watershed transformation, the method described here considers global information of a correlation image to obtain a seam which is connected, irregular and, thus, more realistic than those defined by the existing methods.



Standards related to Image edge detection

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Jobs related to Image edge detection

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