Neural Networks (NNs) are today used for all our daily tasks; instance, in mobile phones. We here want to show how restrict their access privileged users. Our solution relies on a degraded implementation which can be corrected thanks PIN. explain select few parameters an NN so as maximize the gap accuracy between premium and modes. report experiments of proposal deep prove its practicability.

Regularization is commonly used for alleviating overfitting in machine learning. For convolutional neural networks (CNNs), regularization methods, such as DropBlock and Shake-Shake, have illustrated the improvement generalization performance. However, these methods lack a self-adaptive ability throughout training. That is, strength fixed to predefined schedule, manual adjustments are required a...

Deep convolutional neural networks are being actively investigated in a wide range of speech and audio processing applications including speech recognition, audio event detection and computational paralinguistics, owing to their ability to reduce factors of variations, for learning from speech. However, studies have suggested to favor a certain type of convolutional operations when building a d...

In this paper, we propose a deep neural network architecture for object recognition based on recurrent neural networks. The proposed network, called ReNet, replaces the ubiquitous convolution+pooling layer of the deep convolutional neural network with four recurrent neural networks that sweep horizontally and vertically in both directions across the image. We evaluate the proposed ReNet on thre...