This paper describes a hardware implementation of tree classifiers based on a custom VLSI chip and a CPLD chip. The tree classifier comprises a first layer of threshold logic unit, implemented on a reconfigurable custom chip, followed by a logical function implemented using a CPLD chip. We first describe the architecture of tree classifiers and compare its performance with support vector machine (SVM) for different data sets. The reconfigurability of the hardware (number of classifiers, topology and precision) is discussed. Experimental results show that the hardware presents a number of interesting feature such as reconfigurability, as well as improved fault tolerance. © 2004 IEEE
We describe in this work a Core Generator for Pattern Recognition tasks. This tool is able to genera...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
Summarization: The available e-data throughout the Web are growing at such a high rate that data min...
Colloque avec actes et comité de lecture. internationale.International audienceThis paper describe a...
The Gas Identification System (GIS) based on an array of gas sensors and itsrecognition techniques h...
This paper proposes a gas identification system based on the committee machine (CM) classifier, whic...
The problem of tree pattern matching for object recognition in images is computationally intensive i...
The problem of tree pattern matching for object recognition in images is computationally intensive i...
The support vector machine (SVM) is one of the highly powerful classifiers that have been shown to b...
The support vector machine (SVM) is one of the highly powerful classifiers that have been shown to b...
Kernel-based classifiers are neural networks (radial basis functions) where the probability densitie...
Classifying Microarray data, which are of high dimensional nature, requires high computational power...
This paper describes a hardware implementation of threshold network ensembles (TNE) for classificati...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
We describe in this work a Core Generator for Pattern Recognition tasks. This tool is able to genera...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
Summarization: The available e-data throughout the Web are growing at such a high rate that data min...
Colloque avec actes et comité de lecture. internationale.International audienceThis paper describe a...
The Gas Identification System (GIS) based on an array of gas sensors and itsrecognition techniques h...
This paper proposes a gas identification system based on the committee machine (CM) classifier, whic...
The problem of tree pattern matching for object recognition in images is computationally intensive i...
The problem of tree pattern matching for object recognition in images is computationally intensive i...
The support vector machine (SVM) is one of the highly powerful classifiers that have been shown to b...
The support vector machine (SVM) is one of the highly powerful classifiers that have been shown to b...
Kernel-based classifiers are neural networks (radial basis functions) where the probability densitie...
Classifying Microarray data, which are of high dimensional nature, requires high computational power...
This paper describes a hardware implementation of threshold network ensembles (TNE) for classificati...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
We describe in this work a Core Generator for Pattern Recognition tasks. This tool is able to genera...
A gas discrimination system is mainly made of two parts, the sensing part and the processing part. A...
Summarization: The available e-data throughout the Web are growing at such a high rate that data min...