The main thrust of CNN technology has been in analog implementations. Early attempts for digital implementations have a limited potential, confining the usage to for instance linear algorithms for B/W pictures. The paper looks into the prospects of successfully integrating the full CNN potential. This requires a carefully tuning of memory and network-on-chip bandwidth to the temporal/spatial aspects of the neural nodes. The paper introduces an exploration model and discusses architecture with application to streaming grey-scale images
Real-time image processing represents an application field where cellular neural networks best show ...
Computer vision is becoming an increasingly trendy word in the area of image processing. With the em...
Abstract. This paper describes a full-custom mixed-signal chip that embeds digitally programmable an...
Integrated Processors (IP) are meant to supply algorithm-specific cores to a micro-electronic system...
The paper presents design considerations for a digital Cellular Neural Network. The architectural sp...
Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) ...
Computationally hard problems, such as operations on n-dimensional maps, are in need of efficient so...
Image processing is one of the popular applications of Cellular Neural Networks. Macro enriched fiel...
The paper investigates the potential for a packet switching network for real-time image processing b...
This paper presents a CMOS implementation of a layered CNN concurrent with 32times32 photosensors wi...
To computing the correlationcoefficients between two images, this paper proposesan algorithm based o...
Cellular Neural Networks are characterized by simplicity of operation. The network consists of a lar...
This thesis presents the results of an architectural study on the design of FPGA- based architecture...
The state of the art work in cellular neural networks (CNN) has concentrated on VLSI implementations...
Some of the features of the biological retina can be modelled by a cellular neural network (CNN) com...
Real-time image processing represents an application field where cellular neural networks best show ...
Computer vision is becoming an increasingly trendy word in the area of image processing. With the em...
Abstract. This paper describes a full-custom mixed-signal chip that embeds digitally programmable an...
Integrated Processors (IP) are meant to supply algorithm-specific cores to a micro-electronic system...
The paper presents design considerations for a digital Cellular Neural Network. The architectural sp...
Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) ...
Computationally hard problems, such as operations on n-dimensional maps, are in need of efficient so...
Image processing is one of the popular applications of Cellular Neural Networks. Macro enriched fiel...
The paper investigates the potential for a packet switching network for real-time image processing b...
This paper presents a CMOS implementation of a layered CNN concurrent with 32times32 photosensors wi...
To computing the correlationcoefficients between two images, this paper proposesan algorithm based o...
Cellular Neural Networks are characterized by simplicity of operation. The network consists of a lar...
This thesis presents the results of an architectural study on the design of FPGA- based architecture...
The state of the art work in cellular neural networks (CNN) has concentrated on VLSI implementations...
Some of the features of the biological retina can be modelled by a cellular neural network (CNN) com...
Real-time image processing represents an application field where cellular neural networks best show ...
Computer vision is becoming an increasingly trendy word in the area of image processing. With the em...
Abstract. This paper describes a full-custom mixed-signal chip that embeds digitally programmable an...