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Quantized Convolutional Neural Networks for Mobile Devices
TLDR
We propose an efficient framework, namely Quantized CNN, to simultaneously speed-up the computation and reduce the storage and memory overhead of CNN models. Expand
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Efficient Privacy-Preserving Dual Authentication and Key Agreement Scheme for Secure V2V Communications in an IoV Paradigm
TLDR
The Internet of Vehicles (IoV) aims to provide a new convenient, comfortable, and safe driving way, and in turn enables intelligent transportation through wireless communications. Expand
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HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data
TLDR
We developed a novel hybrid approach that combines gene ranking and clustering analysis to select a small set of non-redundant marker genes that are most relevant for the classification task. Expand
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Stacked Deconvolutional Network for Semantic Segmentation
TLDR
We propose a Stacked Deconvolutional Network (SDN) for semantic segmentation. Expand
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R-Histogram: quantitative representation of spatial relations for similarity-based image retrieval
TLDR
R-Histogram extends the histogram of angles by incorporating both angles and labeled distances. Expand
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A novel stationary wavelet denoising algorithm for array-based DNA Copy Number data
TLDR
We propose a novel stationary wavelet denoising scheme based on DWT coefficients for DNA copy number data. Expand
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R*-Histograms: efficient representation of spatial relations between objects of arbitrary topology
TLDR
We propose in this paper the R*-Histogram, a new extension to the R-Histograms, a quantitative representation of spatial relations between objects with more complicated topology, which is asymptotically faster than the original O(N<sup>2</sup>) time algorithm. Expand
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Weakly Supervised RBM for Semantic Segmentation
TLDR
We propose a weakly supervised Restricted Boltzmann Machines (WRBM) approach to deal with the task of semantic segmentation with only image-level labels available. Expand
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Vcash: A Novel Reputation Framework for Identifying Denial of Traffic Service in Internet of Connected Vehicles
TLDR
We propose vehicle cash (Vcash), a reputation framework for identifying denial of traffic service, to resolve the trustworthiness problem in the Internet of Connected Vehicles. Expand
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