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Faking Signals to Fool Deep Neural Networks in AMC via Few Data Points

Hongbin Ma, Shuyuan Yang, Guangjun He, Ruowu Wu, Xiaojun Hao, Tingpeng Li, Zhixi Feng
2021 IEEE Access  
Performance changes with the SNR is displayed in Hongbin Ma et al.: Faking Signals to Fool Deep Neural Networks in AMC via Few Data Points VOLUME 4, 2016  ...  CONCLUSION In this paper, in order to attack AMC classifiers, we propose the FDPA to generate fake signals from real modulation signals, with only a few varied data points.  ... 
doi:10.1109/access.2021.3106704 fatcat:cdrnbsfhy5hnjpf3grswnullkm

Adversarial Machine Learning in Wireless Communications using RF Data: A Review [article]

Damilola Adesina, Chung-Chu Hsieh, Yalin E. Sagduyu, Lijun Qian
2021 arXiv   pre-print
First, the background of AML attacks on deep neural networks is discussed and a taxonomy of AML attack types is provided.  ...  Machine learning (ML) provides effective means to learn from spectrum data and solve complex tasks involved in wireless communications.  ...  BACKGROUND OF DEEP ADVERSARIAL LEARNING A. Deep Neural Network Supervised learning using a DNN is expressed as a mapping f that models the mapping from the input data to a class (label).  ... 
arXiv:2012.14392v2 fatcat:4d3x2scwjvh33drc745mmc4gvy

Style-based quantum generative adversarial networks for Monte Carlo events [article]

Carlos Bravo-Prieto, Julien Baglio, Marco Cè, Anthony Francis, Dorota M. Grabowska, Stefano Carrazza
2021 arXiv   pre-print
The new quantum generator architecture leads to an improvement in state-of-the-art implementations while maintaining shallow-depth networks.  ...  We validate this methodology by implementing the quantum network on artificial data generated from known underlying distributions.  ...  The authors acknowledge the support of the CloudBank EU as a pilot brokering cloud service at CERN, allowing for access to Amazon Web Services in order to run our algorithm on IonQ hardware.  ... 
arXiv:2110.06933v1 fatcat:zzyymjalbfbmjcz6iz5uloou54

Video Prediction with Appearance and Motion Conditions [article]

Yunseok Jang, Gunhee Kim, Yale Song
2018 arXiv   pre-print
We propose an Appearance-Motion Conditional GAN to address this challenge.  ...  Video prediction aims to generate realistic future frames by learning dynamic visual patterns.  ...  Acknowledgements We thank Kang In Kim for helpful comments about building a human evaluation page.  ... 
arXiv:1807.02635v1 fatcat:55akdl6wvrdtbjwefsqdv6lnzy

Machine Learning in NextG Networks via Generative Adversarial Networks [article]

Ender Ayanoglu and Kemal Davaslioglu and Yalin E. Sagduyu
2022 pre-print
In this paper, we investigate their use in next-generation (NextG) communications within the context of cognitive networks to address i) spectrum sharing, ii) detecting anomalies, and iii) mitigating security  ...  Generative Adversarial Networks (GANs) are Machine Learning (ML) algorithms that have the ability to address competitive resource allocation problems together with detection and mitigation of anomalous  ...  ACKNOWLEDGMENTS The authors would like to thank the anonymous reviewers whose comments improved the presentation in the paper.  ... 
doi:10.1109/tccn.2022.3153004 arXiv:2203.04453v1 fatcat:uybib5kzvnf3llno25ezbwv3gm

Dual-Attention Generative Adversarial Network and Flame and Smoke Analysis [article]

Yuchuan Li, University, My
The Color2IR Conversion module is made by deep neural networks to convert RGB video frames into InfraRed (IR) frames, which could provide important thermal information of fire.  ...  However, data from advanced vision devices or sensors can be analyzed by applying deep learning beyond auxiliary methods in data processing and analysis.  ...  Deep neural networks could also help in the conversion of RGB images to IR images.  ... 
doi:10.20381/ruor-26991 fatcat:zz5cn43q3zfqxpoeojb3dsunma

16th ISoP Annual Meeting ''Pharmacovigilance for Safer Tomorrow'' Agra, India 16–19 October, 2016

2016 Drug Safety  
There is growing concern to assess the ADRs which is a hindrance in achieving successful remission.  ...  Patient demographics, clinical and drug data, details of ADR, onset time, causal drug details, outcome and severity were collected as per CDSCO-ADR reporting form.  ...  The analysis of NET has detected the signal of Neural tube defects due to fenugreek. This signal was the subject of studies and lead to risk minimization actions.  ... 
doi:10.1007/s40264-016-0445-6 pmid:27612845 fatcat:6tev4gmnyfcjpc5pfsa6ljt434

Collider Physics within the Standard Model: a Primer [article]

Guido Altarelli
2013 arXiv   pre-print
I hope that these lectures can provide an introduction to the subject for the interested reader, assumed to be already familiar with quantum field theory and some basic facts in elementary particle physics  ...  as taught in undergraduate courses.  ...  An alternative way to cope with the gluon problem is to drastically suppress the gluon parametrization rigidity by adopting the neural network approach. With this method, in ref.  ... 
arXiv:1303.2842v2 fatcat:nughlbnbyrfpnom24iessgbk54

Methods for data-related problems in person re-ID

Sara Iodice, Krystian Mikolajczyk, FACER2VM
very challenging due to significant misalignment of the views. 2) Low diversity in training data introduces bias in re-ID systems. 3) The available data might come from different modalities, e.g., text  ...  The thesis also investigates different types of bias that typically occur in re-ID scenarios when the similarity between two persons is due to the same pose, body part, or camera view, rather than to the  ...  The goal is to train a differentiable function G, usually represented by deep neural networks, to generate fake samples from seeds z as close as possible to the real data x.  ... 
doi:10.25560/87153 fatcat:tvn2lto3ffdutgj62oyutv7bwi

EmTract: Investor Emotions and Market Behavior [article]

Domonkos Vamossy, Rolf Skog
We develop a tool that extracts emotions from social media text data. Our methodology has three main advantages.  ...  Third, increased investor enthusiasm prior to the IPO contributes to the large first-day return and long-run underperformance of IPO stocks.  ...  B.2.5 Linear Layer, Neural Network and Softmax Activation Our next step is to apply another set of weights and bias terms and pass it to two-layered Neural Network: O t = H t W h,q + b q (10) D = σ d (  ... 
doi:10.48550/arxiv.2112.03868 fatcat:m5rbp7vf75apvfcq5qdbbezzcq

MARKETING OF INNOVATIONS & INNOVATIONAL MARKETING Teaching manual for students of economic majors

Yu Ossik, Z Borbasova, O Prokopenko, V Valeeva
multimedia services in networks of the third generation (3G), data transmission via Bluetooth and IR port, advertising inclusion to navigation systems (GPS), etc.  ...  The social networking site provides the expert in marketing with demographic data about clients when they are in a network.  ...