In order to get real time image processing for mobile robot vision, we propose to use a discrete time Cellular Neural Network implementation by a convolutional structure on Altera FPGA using VHDL language. We obtain at least 9 times faster processing than other emulations for the same problem
Summary. Real time image processing requires processing huge amounts of data in a very short time. H...
Abstract—Recent developments in smartphones create an ideal platform for robotics and computer visio...
Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a par...
In previous works [1, 2] we developed a visual servoing platform using C language to extract the req...
An FPGA architecture to emulate a single-layer Cellular Neural Network - Universal Machine (CNN-UM) ...
Convolutional Neural Networks (CNNs) allow fast and precise image recognition. Nowadays this capabil...
for image processing on the Field Programmable Gate Array (FPGA) and it’s experiment results are pre...
Computationally hard problems, such as operations on n-dimensional maps, are in need of efficient so...
Abstract — In this paper an FPGA based Implementation of a 1D-CNN with a 3×1 template and 8×1 length...
Convolutional Neural Networks (CNNs) are a variation of feed-forward Neural Networks inspired by the...
Cellular Neural Networks are characterized by simplicity of operation. The network consists of a lar...
Many recent visual recognition systems can be seen as being composed of multiple layers of convoluti...
Abstract. A time critical process in a real-time mobile robot application such as RoboCup, is the de...
In this presentation, we report the results of applying a binarised Convolutional Neural Network (CN...
Convolutional Neural Network (CNN) has been extensively used for image recognition due to its great ...
Summary. Real time image processing requires processing huge amounts of data in a very short time. H...
Abstract—Recent developments in smartphones create an ideal platform for robotics and computer visio...
Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a par...
In previous works [1, 2] we developed a visual servoing platform using C language to extract the req...
An FPGA architecture to emulate a single-layer Cellular Neural Network - Universal Machine (CNN-UM) ...
Convolutional Neural Networks (CNNs) allow fast and precise image recognition. Nowadays this capabil...
for image processing on the Field Programmable Gate Array (FPGA) and it’s experiment results are pre...
Computationally hard problems, such as operations on n-dimensional maps, are in need of efficient so...
Abstract — In this paper an FPGA based Implementation of a 1D-CNN with a 3×1 template and 8×1 length...
Convolutional Neural Networks (CNNs) are a variation of feed-forward Neural Networks inspired by the...
Cellular Neural Networks are characterized by simplicity of operation. The network consists of a lar...
Many recent visual recognition systems can be seen as being composed of multiple layers of convoluti...
Abstract. A time critical process in a real-time mobile robot application such as RoboCup, is the de...
In this presentation, we report the results of applying a binarised Convolutional Neural Network (CN...
Convolutional Neural Network (CNN) has been extensively used for image recognition due to its great ...
Summary. Real time image processing requires processing huge amounts of data in a very short time. H...
Abstract—Recent developments in smartphones create an ideal platform for robotics and computer visio...
Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a par...