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Jeffrey Kingyens, J. Gregory Steffan
We propose a soft processor programming model and architecture inspired by graphics processing units (GPUs) that are well-matched to the strengths of FPGAs, namely, highly parallel and pipelinable computation. In particular, our soft processor architecture exploits multithreading, vector operations, and predication to supply a floating-point pipeline of 64 stages via hardware support for up to […]
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Li Cheng, Minglun Gong
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over time. In this paper, we formulate the problem mathematically as minimizing a constrained risk functional motivated from the large margin principle. It is a generalization of the one class […]
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Claude Kauffmann, Nicolas Piche
PURPOSE: We present a GPU-based framework to perform organ segmentation in N-dimensional (ND) medical image datasets by computation of weighted distances using the Ford-Bellman algorithm (FBA). Our GPU implementation of FBA gives an alternative and optimized solution to other graph-based segmentation techniques. METHODS: Given a number of K labelled-seeds, the segmentation algorithm evolves and segments […]
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