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2021 IEEE Photovoltaic Specialists Conference (PVSC)
Photovoltaic materials, devices, systems and related science and technology
2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting
The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science
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
The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.
ECTC is the premier international conference sponsored by the IEEE Components, Packaging and Manufacturing Society. ECTC paper comprise a wide spectrum of topics, including 3D packaging, electronic components, materials, assembly, interconnections, device and system packaging, optoelectronics, reliability, and simulation.
IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.
Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission
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 ...
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.
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-- ...
2018 21st Euromicro Conference on Digital System Design (DSD), 2018
Lucas-Kanade (LK) optical flow algorithm is widely used for moving object detection and tracking by computing the motion vectors of pixels in image sequences. Due to the high computation complexity, optical flow computation is one of the crucial operations in many computer vision applications. This paper presents a low-cost hardware implementation of the LK optical flow algorithm. In particular, we ...
2012 Fifth International Conference on Intelligent Networks and Intelligent Systems, 2012
For the problem of low detection accuracy and slow speed to fast motion object, when solving the basic optical flow constraint equation with the traditional algorithm, an improved optical flow algorithm based on LK optical flow algorithm has been put forward in this paper. The intensive optical flow is the biggest characteristic of the algorithm, the structure of the sampling ...
2017 3rd IEEE International Conference on Computer and Communications (ICCC), 2017
Optical flow algorithm is an important approach to estimate motion from image sequence. Using it can effectively analyze the dynamic information of facial expressions and extract the characteristic flow which can reflect the facial expression changes. In this paper, based on the Lucas-Kanade optical flow algorithm, the Hession matrix is introduced to filter the unreliable constraint points in the local ...
2018 4th International Conference on Control, Automation and Robotics (ICCAR), 2018
The Optical Flow computation is the estimation of the apparent displacement of the object on an image sequence (actual image and next image). There are different methods for Optical Flow estimation, standing out exhaustive methods and differential methods. Differential Methods propose a model that considers the error in the Optical flow estimation. This model is minimized solving the Euler-Lagrange equations ...
2010 International Conference on Electrical and Control Engineering, 2010
In this paper we develop a novel approach called the compensated HS (CHS) optical flow estimation algorithm to improve the precision of the large displacement optical flow field. For the lack of the higher order term in the optical flow constraint equation, the traditional optical flow estimation based on the first-order gradient always produce the optical flow field with obvious ...
Switching, Routing & Forwarding: Technical Session 1 - HPSR 2020 Virtual Conference
IMS 2011 Microapps - Ultra Low Phase Noise Measurement Technique Using Innovative Optical Delay Lines
Multi-Level Optimization for Large Fan-In Optical Logic Circuits - Takumi Egawa - ICRC 2018
Micro-Apps 2013: Integrated Electro-Thermal Design of a SiGe PA
On-chip Passive Photonic Reservoir Computing with Integrated Optical Readout - IEEE Rebooting Computing 2017
Multi-Level Optical Weights in Integrated Circuits - IEEE Rebooting Computing 2017
Spatial-Spectral Materials for High Performance Optical Processing - IEEE Rebooting Computing 2017
An Energy-efficient Reconfigurable Nanophotonic Computing Architecture Design: Optical Lookup Table - IEEE Rebooting Computing 2017
Demonstration of a Coherent Tunable Amplifier for All-Optical Ising Machines: IEEE Rebooting Computing 2017
Towards On-Chip Optical FFTs for Convolutional Neural Networks - IEEE Rebooting Computing 2017
MicroApps: A Streamlined Design Flow Featuring AWR Microwave Offce and Ansys HFSS (AWR)
MicroApps: Radar Design Flow with NI-AWR Integrated Framework (National Instruments)
PA Design: RF Boot Camp
An Integrated Optical Parallel Multiplier Exploiting Approximate Binary Logarithms - Jun Shiomi - ICRC 2018
APEC Speaker Highlights - Doug Hopkins, University of Buffalo, Power Electronics/Smart-Grid
MicroApps: Making the Transition from AWR to Cadence Tools - A More Seamless & Effcient Flow for Mutual IC & PCB Customers (AWR)
Scalable and Reconfigurable Tap-Delay-Line for Multichannel Equalization - Ari Willner - Closing Ceremony, IPC 2018
IEEE Themes - Efficient networking services underpin social networks
Robotics History: Narratives and Networks Oral Histories: Masaru Uchiyama
Lucas-Kanade (LK) optical flow algorithm is widely used for moving object detection and tracking by computing the motion vectors of pixels in image sequences. Due to the high computation complexity, optical flow computation is one of the crucial operations in many computer vision applications. This paper presents a low-cost hardware implementation of the LK optical flow algorithm. In particular, we design a low-cost divider used in the matrix inversion, leading to significant reduction in delay and area for calculation of small optical flow vectors. Furthermore, we also design a pyramidal LK optical flow computation unit that can process images of different sizes in order to increase the magnitude range of optical flow vectors.
For the problem of low detection accuracy and slow speed to fast motion object, when solving the basic optical flow constraint equation with the traditional algorithm, an improved optical flow algorithm based on LK optical flow algorithm has been put forward in this paper. The intensive optical flow is the biggest characteristic of the algorithm, the structure of the sampling pyramid executive optical flow, the second from bottom to date, and the second from bottom optical flow numerical multiply 2, through the double linear interpolation get the bottom of the optical flow. In the final layer iterative initialization, set specific optical flow threshold value, before a layer of iterative result for less than the response of the threshold value point, known as moving range too small point, it directly set the optical flow number to zeros and skip this point, reduce the computation time. The results shows that this improved optical flow algorithm, which can accurately analysis and forecast in the scene or particular movement of the target of the campaign mode, has the advantages of not only a high precision of motion estimation and a strong anti-interference, but also a better speed compared with the tradition optical flow algorithm.
Optical flow algorithm is an important approach to estimate motion from image sequence. Using it can effectively analyze the dynamic information of facial expressions and extract the characteristic flow which can reflect the facial expression changes. In this paper, based on the Lucas-Kanade optical flow algorithm, the Hession matrix is introduced to filter the unreliable constraint points in the local neighborhood and improve the accuracy of the optical flow field in facial expression changes. Experimental results show the proposed method offers a better performance for the Lucas-Kanade optical flow algorithm.
The Optical Flow computation is the estimation of the apparent displacement of the object on an image sequence (actual image and next image). There are different methods for Optical Flow estimation, standing out exhaustive methods and differential methods. Differential Methods propose a model that considers the error in the Optical flow estimation. This model is minimized solving the Euler-Lagrange equations of linearized versions of the functional terms like in the differential model developed by Horn & Schunck. The exhaustive methods take a point and his environment in the actual image and search for the more similar in the next image like in the Steinbücker model of Exhaustive Search. In this paper is presented the implementation of the differential methods of Horn & Schunck and the Steinbücker's exhaustive “variational” method. Additionally it is posed a new method that combines the differential method and the exhaustive one. With the use of the integral image and a cost volume it manages to obtain a processing time reduction of the exhaustive methods close to a 98% in comparison to a similar implementation in Matlab. Through the implementation of the combined methods it is possible to reach below 15 degrees in average angular error (AAE).
In this paper we develop a novel approach called the compensated HS (CHS) optical flow estimation algorithm to improve the precision of the large displacement optical flow field. For the lack of the higher order term in the optical flow constraint equation, the traditional optical flow estimation based on the first-order gradient always produce the optical flow field with obvious error in the case of large image displacement. We compensate the optical flow constraint equation with the fitted higher-order term through matching the corner points extracted by the Harris detector. And then, we use it to construct the new energy function and derive the new Gauss-Seidel iterative solution of the optical flow. To the existence of multi-motion pattern, we adopt k-means algorithm to cluster these pattern and point-by- point fit the higher order terms of different pattern. The final experiments show that this algorithm could obviously improve the precision of the large displacement optical flow and of the optical flow in the smooth region.
An improved registration method of multimodal brain images combined optical flow and Speeded-Up Robust Features (SURF) is presented in this paper. Firstly, histogram specification is used to transform modal of images before registration, the similar modal of images are beneficial to the following image registration. Secondly, the feature points are extracted by SURF, and then the preliminary registered image could be obtained. Thirdly, with the obtained registered image, optical flow algorithm is used to achieve the accurate results. Finally, several typical multimodal brain images are employed to evaluate the performances of the proposed approach, Demons based method, SURF based method and Mutual Information (MI) based method. Experimental results show that the measure indexes of Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) and correlation coefficient (Rcc) of our method are more competitive compared with the other methods, which indicate the proposed approach has the higher accuracy and better robustness.
This paper presents the using of adaptive Lorentzian influence with the global method optical flow for noise resistance on the visual progression. In particular, optical flow is the pattern of apparent motion of image objects between two consecutive frames caused by the movement of object or camera. It is 2D vector field where each vector is a displacement vector showing the movement of points from the first frame to second. When the image flow is degraded by noise, the performance for approximating the vector in optical flow is incorrect. With adaptive Lorentzian influence, we ensure more desirable noise resistance in global method optical flow in our experiment. We also test the using of adaptive Lorentzian influence over many noise resistance models when they proceed on global method optical flow. Many intensities of the additive white Gaussian (AWG) noise from low to high intensity of noise are utilized in our experiment to ensure our proposed method.
Video Surveillance has become an issue of utmost importance due to rising crime and violence rate in the world. Many algorithms exist to analyze the behavior of the moving objects. In this paper, an approach to detect any violent behavior in videos using optical flow algorithms. The SDHA 2000 dataset is used to analyze foreground behavior. The main task in violence detection is to detect moving objects and classify their behavior using mean of intensity as violent or non-violent.
In order to enable the optical flow to track larger and faster moving targets, pyramid Lucas-Kanade optical flow method is used to detect and track moving targets. First, detecting the corners which is easy to track, in order to improve the tracking accuracy, detected corners and then calculate the sub- pixel corner, and then the video in each frame of the image layered in the image pyramid to calculate the optical flow at the top corner, use the next pyramid as the starting point of the pyramid and repeat this process until the bottom pyramid image, which can overcome the Lucas-Kanade optical flow method cannot track faster and larger movements the shortcomings, to achieve the tracking of moving goals.
This paper proposed a moving vehicle detection algorithm based on optical flow estimation on an edge image. Using the Canny operator, the image edge is obtained and refined. Then a set of feature points is extracted from the edge image. The pyramid model of Lucas-Kanade optical flow is used to calculate the optical flow information of the feature point set. A new algorithm, which is called the weighted Kmeans optical flow clustering algorithm, is proposed to cluster feature points and used to identify vehicle pattern of the feature point set on the optical flow so that the moving vehicle can be efficiently extracted from the complicated dynamic background. In this paper the vehicle videos, which are captured by a camera on a moving car, are used as the test data set. The experimental results show that this algorithm can effectively detect the moving vehicles in the videos from the camera on the moving car.
This guide provides recommendations for loading mineral-oil-immersed transformers and voltage regulators with insulation systems rated for a 65°C average winding temperature rise at rated load. This guide applies to transformers manufactured in accordance with IEEE C57.12.00 and tested in accordance with IEEE C57.12.90, and voltage regulators manufactured and tested in accordance with C57.15. Because a substantial population of transformers and ...
IEEE Draft Standard for Information Technology - Telecommunications and Information Exchange Between Systems - Local and Metropolitan Area Networks - Specific Requirements Part 3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) Access Method and Physical Layer Specifications - Amendment: MAC Control Frame for Priority-based Flow Control
This standard defines a MAC Control Frame to support 802.1Qbb Priority-based Flow Control. Data Center Bridging networks (bridges and end nodes) are characterized by limited bandwidth-delay product and limited hop-count. Traffic class is identified by the VLAN tag priority values. Priority-based flow control is intended to eliminate frame loss due to congestion. This is achieved by a mechanism similar to ...
The packet protocol described by this standard allows a device to carry on multiple, concurrent exchanges of data and/or control information with another device across a single point-to-point link. the protocol is not a device control language. The protocol provides basic transportlevel flow control and multiplexing services. The multiplexed information exchanges are independent and blocking of one has no effect ...
Physical connectors and cables, electrical properties, and logical protocols for point to point serial scaleable interconnect, operating at speeds of 10-200 Mbit/sec and at 1 Gbit/sec in copper and optic technologies (as developed in Open Microprocessor systems Initiative/heterogeneous InterConnect Project (OMI/HIC).