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Asgeir Bjorgan
Hyperspectral imaging with a high spatial and spectral resolution can be used to analyze materials using spectroscopic methods. This can be applied on skin as a general purpose real-time diagnostic tool. Light transport models, like the diffusion model, can describe the light propagation in tissue before the light is captured by the hyperspectral camera. The […]
Dariusz Konieczny, Karol Radziszewski
In this paper we are testing the efficiency of parallelization with use of graphic cards. There are many applications where such systems occurs in common, so we choose the domain of artificial neural networks. Actually sold graphic cards gives us strong potential in speeding up calculations and card vendors provide us with even more, giving […]
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Revanth N R, P. J. Narayanan
Graphics models are getting increasingly bulkier with detailed geometry, textures, normal maps, etc. There is a lot of interest to model and navigate through detailed models of large monuments. Many monuments of interest have both rich detail and large spatial extent. Rendering them for navigation on a single workstation is practically impossible, even given the […]
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Dave Cunningham, Rajesh Bordawekar, Vijay Saraswat
GPU architectures have emerged as a viable way of considerably improving performance for appropriate applications. Program fragments (kernels) appropriate for GPU execution can be implemented in CUDA or OpenCL and glued into an application via an API. While there is plenty of evidence of performance improvements using this approach, there are many issues with productivity. […]
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Vincent Garcia, Eric Debreuve, Frank Nielsen, Michel Barlaud
The k-nearest neighbor (kNN) search problem is widely used in domains and applications such as classification, statistics, and biology. In this paper, we propose two fast GPU-based implementations of the brute-force kNN search algorithm using the CUDA and CUBLAS APIs. We show that our CUDA and CUBLAS implementations are up to, respectively, 64X and 189X […]

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