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Deep Convolutional Neural networks (ConvNets) have achieved impressive results in several applications of computer vision and speech processing. With the availability of a large training set, it is common to find that the set contains useless samples (instances), either redundant or noisy. The process of removing these instances is called instance selection(More)
Recent advancements in deep Convolutional Neural Networks (CNNs) have led to impressive progress in computer vision, especially in image classification. CNNs involve numerous hyperparameters that identify the network's structure such as depth of the network, kernel size, number of feature maps, stride, pooling size and pooling regions etc. These(More)
In any security system, there are many security issues that are related to either the sender or the receiver of the message. Quantum computing has proven to be a plausible approach to solving many security issues such as eavesdropping, replay attack and man-in-the-middle attack. In the e-voting system, one of these issues has been solved, namely, the(More)
Recent advances in Convolutional Neural Networks (CNNs) have obtained promising results in difficult deep learning tasks. However, the success of a CNN depends on finding an architecture to fit a given problem. A hand-crafted architecture is a challenging, time-consuming process that requires expert knowledge and effort, due to a large number of(More)
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