Device and method to process data in parallel
A method and apparatus for processing data are provided. The processor includes an input
buffer, a data extractor, a multiplier, and an adder. The input buffer receives data and stores …
buffer, a data extractor, a multiplier, and an adder. The input buffer receives data and stores …
[图书][B] Algorithms for efficient computation of convolution
Convolution is an important mathematical tool in both fields of signal and image processing.
It is employed in filtering [1, 2], denoising [3], edge detection [4, 5], correlation [6] …
It is employed in filtering [1, 2], denoising [3], edge detection [4, 5], correlation [6] …
[PDF][PDF] FPGA-based acceleration for convolutional neural networks on PYNQ-Z2
TV Huynh - Int. J. Comput. Digit. Syst, 2022 - pdfs.semanticscholar.org
Convolutional neural network is now widely used in computer vision and deep learning
applications. The most computeintensive layer in convolutional neural networks is the …
applications. The most computeintensive layer in convolutional neural networks is the …
A multiwindow partial buffering scheme for FPGA-based 2-D convolvers
H Zhang, M Xia, G Hu - … Transactions on Circuits and Systems II …, 2007 - ieeexplore.ieee.org
Two-dimensional (2-D) convolution is widely used in image and video processing. Although
the operation is simple, 2-D convolution is however both computationally expensive and …
the operation is simple, 2-D convolution is however both computationally expensive and …
Double MAC on a DSP: Boosting the performance of convolutional neural networks on FPGAs
Deep learning workloads, such as convolutional neural networks (CNNs) are important due
to increasingly demanding high-performance hardware acceleration. One distinguishing …
to increasingly demanding high-performance hardware acceleration. One distinguishing …
A new approach for design of an efficient FPGA-based reconfigurable convolver for image processing
Two-dimensional convolution plays a fundamental role in different image processing
applications. Image convolving with different kernel sizes enriches the overall performance …
applications. Image convolving with different kernel sizes enriches the overall performance …
An area-efficient 2-D convolution implementation on FPGA for space applications
The 2-D Convolution is an algorithm widely used in image and video processing. Although
its computation is simple, its implementation requires a high computational power and an …
its computation is simple, its implementation requires a high computational power and an …
Towards an embedded biologically-inspired machine vision processor
Biologically-inspired machine vision algorithms-those that attempt to capture aspects of the
computational architecture of the brain-have proven to be a promising class of algorithms for …
computational architecture of the brain-have proven to be a promising class of algorithms for …
Optimizing image processing on multi-core CPUs with Intel parallel programming technologies
CG Kim, JG Kim, DH Lee - Multimedia tools and applications, 2014 - Springer
The rapid advance of computer hardware and popularity of multimedia applications enable
multi-core processors with sub-word parallelism instructions to become a dominant market …
multi-core processors with sub-word parallelism instructions to become a dominant market …
FPGA-based architecture for the real-time computation of 2-D convolution with large kernel size
FJ Toledo-Moreo, JJ Martínez-Alvarez… - Journal of Systems …, 2012 - Elsevier
Bidimensional convolution is a low-level processing algorithm of interest in many areas, but
its high computational cost constrains the size of the kernels, especially in real-time …
its high computational cost constrains the size of the kernels, especially in real-time …