Abstract: Convolution is a formal mathematical operation, just as multiplication, addition, and integration. Addition takes two numbers and produces a third number, while convolution takes two signals and produces a third signal. Convolution is used in the mathematics of many fields, such as probability and statistics. In linear systems, convolution is used to describe the relationship between three signals of interest: the input signal, the impulse response, and the output signal. Vedic mathematics is used since it reduces time, increases speed and is easy to implement. It helps to solve problem 10-15 times faster. It covers explanation of several mathematical terms such as algebra, arithmetic, geometry etc. This paper presents a direct me...
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the h...
Abstract: This paper continues a previous work on the design and implementation of a real time, sin-...
Recent years, with the development of Convolution Neural Networks (CNN), machine learning has achiev...
We present original approach to the design and implementation of the convolution in this article. Th...
This paper presents a direct method of reducing convolution processing time using hardware computing...
Digital signal processing. In Digital Signal Processing, the convolution and deconvolution with a v...
Abstract — In Digital Signal Processing, the convolution and deconvolution with a very long sequenc...
The aim of this work is to provide a practical solution to the computation intensive convolution tas...
Digital signal processing, Digital control systems, Telecommunication, Audio and Video processing ar...
Hardware-based acceleration is an extensive attempt to facilitate many computationally-intensive mat...
Abstract. Convolution is a very important operation within artificial vision. It can be characterize...
The Digital Image Processing convolution is core block for Convolution Neural Networks (CNN) which i...
In this paper, we present an implementation of areal-time convolver, based on Field Programmable Gat...
[[abstract]]This paper describes a design of adjustable convolutional hardware in image processing. ...
We present original approach to the design and implementation of the convolution computing unit in t...
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the h...
Abstract: This paper continues a previous work on the design and implementation of a real time, sin-...
Recent years, with the development of Convolution Neural Networks (CNN), machine learning has achiev...
We present original approach to the design and implementation of the convolution in this article. Th...
This paper presents a direct method of reducing convolution processing time using hardware computing...
Digital signal processing. In Digital Signal Processing, the convolution and deconvolution with a v...
Abstract — In Digital Signal Processing, the convolution and deconvolution with a very long sequenc...
The aim of this work is to provide a practical solution to the computation intensive convolution tas...
Digital signal processing, Digital control systems, Telecommunication, Audio and Video processing ar...
Hardware-based acceleration is an extensive attempt to facilitate many computationally-intensive mat...
Abstract. Convolution is a very important operation within artificial vision. It can be characterize...
The Digital Image Processing convolution is core block for Convolution Neural Networks (CNN) which i...
In this paper, we present an implementation of areal-time convolver, based on Field Programmable Gat...
[[abstract]]This paper describes a design of adjustable convolutional hardware in image processing. ...
We present original approach to the design and implementation of the convolution computing unit in t...
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the h...
Abstract: This paper continues a previous work on the design and implementation of a real time, sin-...
Recent years, with the development of Convolution Neural Networks (CNN), machine learning has achiev...