Add to ORKG225-231This paper presents a novel embedded system for the online training of kernel fuzzy c-means (KFCM) algorithm. A hardware architecture capable of accelerating the KFCM training process is proposed. The architecture is used as a coprocessor in the embedded system. It consists of efficient circuits for the computation of kernel functions, membership coefficients and cluster centers. In addition, the usual iterative operations for updating the membership matrix and cluster centers are merged into one single updating process to evade the large storage requirement. Experimental results show that the proposed solution is an effective alternative for image segmentation with low computational cost and low segmentation error rate
Abstract. This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM b...
Virtually every sector of business and industry that use computing, including financial analysis, se...
In mapping the k-means algorithm to FPGA hardware, we examined algorithm level transforms that drama...
This paper presents a novel VLSI architecture for image segmentation. The architecture is based on t...
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networ...
The growing need for smart surveillance solutions requires that modern video capturing devices to be...
Computational Intelligence Methods have been expanding to industrial applications motivated by thei...
In this paper, a design of a synthesizable hardware model for a Convolutional Neural Network (CNN) i...
[[abstract]]A novel hardware architecture for c-means clustering is presented in this paper. Our arc...
In this paper we present an innovative and high performance embedded system for real-time pattern ma...
A novel k-winners-take-all (k-WTA) competitive learning (CL) hardware architecture is presented for ...
Image segmentation has been an intriguing area for research and developing efficient algorithms, pla...
The goal of the master thesis is to investigate the feasibility ofhaving distributed machine learnin...
Caffe is a deep learning framework, originally developed at UC Berkeley and widely used in large-sca...
Abstract. Bias-corrected fuzzy c-means (BCFCM) algorithm with spatial information has been proven ef...
Abstract. This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM b...
Virtually every sector of business and industry that use computing, including financial analysis, se...
In mapping the k-means algorithm to FPGA hardware, we examined algorithm level transforms that drama...
This paper presents a novel VLSI architecture for image segmentation. The architecture is based on t...
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networ...
The growing need for smart surveillance solutions requires that modern video capturing devices to be...
Computational Intelligence Methods have been expanding to industrial applications motivated by thei...
In this paper, a design of a synthesizable hardware model for a Convolutional Neural Network (CNN) i...
[[abstract]]A novel hardware architecture for c-means clustering is presented in this paper. Our arc...
In this paper we present an innovative and high performance embedded system for real-time pattern ma...
A novel k-winners-take-all (k-WTA) competitive learning (CL) hardware architecture is presented for ...
Image segmentation has been an intriguing area for research and developing efficient algorithms, pla...
The goal of the master thesis is to investigate the feasibility ofhaving distributed machine learnin...
Caffe is a deep learning framework, originally developed at UC Berkeley and widely used in large-sca...
Abstract. Bias-corrected fuzzy c-means (BCFCM) algorithm with spatial information has been proven ef...
Abstract. This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM b...
Virtually every sector of business and industry that use computing, including financial analysis, se...
In mapping the k-means algorithm to FPGA hardware, we examined algorithm level transforms that drama...