B. Krishnamurthy

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In this paper we present a hardware accelerated real-time implementation of deep convolutional neural networks (DCNNs). DCNNs are becoming popular because of advances in the processing capabilities of general purpose processors. However, DCNNs produce hundreds of intermediate results whose constant memory accesses result in inefficient use of general(More)
Sharing images might prompt presentation of individual data and security breach. This collected data can be misused by unsafe clients. To anticipate such sort of undesirable acknowledgement of individual images, adaptable security settings are required. Recently, such security settings are made accessible and keeping up these measures is a cloudy and error(More)
Gokhale, Vinayak A. M.S.E.C.E, Purdue University, August 2014. nn-X A Hardware Accelerator for Convolutional Neural Networks. Major Professor: Eugenio Culurciello. Convolutional neural networks (ConvNets) are hierarchical models of the mammalian visual cortex. These models have been increasingly used in computer vision to perform object recognition and full(More)
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