Abstract
This proceeding is compiled from our previous works, where architecture of the Second-Generation Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v2) was proposed. The system is designed for applications where high-resolution and high-speed is desired. The structure is fully-pipelined and the processing is real-time. Proposed structure is coded in VHDL and realized on two FPGA devices: one high-end and one low-budget. The system is the only reported CNN implementation supporting real-time Full-HD video image processing, to date.
Keywords
Computer science
Field-programmable gate array
VHDL
Cellular neural network
Artificial neural network
Embedded system
Convolutional neural network
Computer architecture
Image processing
Computer hardware
Real-time computing
Image (mathematics)
Artificial intelligence
Subject Areas
Neural Networks Stability and Synchronization
·Computer Networks and Communications ·Physical Sciences
Advanced Memory and Neural Computing
·Electrical and Electronic Engineering ·Physical Sciences
Neural Networks and Applications
·Artificial Intelligence ·Physical Sciences
Citations by Year
2013: 1
2014: 3
2015: 1
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