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A Novel Use of Kernel Discriminant Analysis as a Higher-Order Side-Channel Distinguisher [chapter]

Xinping Zhou, Carolyn Whitnall, Elisabeth Oswald, Degang Sun, Zhu Wang
2018 Lecture Notes in Computer Science  
A recent proposal (presented at Cardis 2016 [6]) aims to bypass the need for explicit enumeration of the (d + 1)tuples without recourse to heuristics, using Kernel Discriminant Analysis (KDA) [15] .  ...  Analysis, Side Channel Distinguisher ity of such attacks began to become apparent with the work of Kocher et al. in the late 1990s [11] .  ...  Martin for the fruitful discussions on the complexity analysis. This work was supported by the National Natural Science Foundation of China (No.61372062) and by the EPSRC (EP/N011635/1).  ... 
doi:10.1007/978-3-319-75208-2_5 fatcat:nrmo67rktbfinfipx6ovgliray

Multiscale Residual Attention Network for Distinguishing Stationary Humans and Common Animals under Through-wall Condition using Ultra-wideband Radar

Yangyang Ma, Fugui Qi, Pengfei Wang, Fulai Liang, Hao Lv, Xiao Yu, Zhao Li, Huijun Xue, Jianqi Wang, Yang Zhang
2020 IEEE Access  
This work proposed a novel multiscale residual attention network for distinguishing between stationary humans and common animals under a through-wall condition based on ultra-wideband radar, which is yet  ...  The overall architecture of the proposed method differed from conventional deep learning methods as it is constructed by parallel 3 × 3 and 5 × 5 kernels incorporated with the residual attention learning  ...  The five blocks with specific channel numbers in the feature extractor are used to extract discriminative feature representations.  ... 
doi:10.1109/access.2020.3006834 fatcat:yfmli5hvtnaf3cl2kpy3mqja2a

Temporal based EEG Signals Classification for Talocrural and Knee Joint Movements using Emotive Head Set
, ,

Anjum Naeem Malik, Javaid Iqbal, Mohsin I Tiwana
2015 Journal of Biomedical Engineering and Medical Imaging  
Fourteen channel Emotive EPOC head set is used to acquire EEG signals from sensorimotor cortex area of brain, using a particular data acquisition timeline protocol.  ...  The paper uses Quadratic discriminant analysis, Naïve Bayes and Support vector machine classifiers to stratify the movement intent of lower limb.  ...  This paper used Quadratic Discriminant Analysis (QDA), Naïve Bayes and one to one support vector machine (SVM) [12] & [14] with quadratic kernel.  ... 
doi:10.14738/jbemi.26.1730 fatcat:co6l6xhirbfhhpuqtl67afesuu

Multichannel-Kernel Canonical Correlation Analysis for Cross-View Person Reidentification

Giuseppe Lisanti, Svebor Karaman, Iacopo Masi
2017 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
For each feature, Kernel Canonical Correlation Analysis (KCCA) with different kernels is exploited to learn several projection spaces in which the appearance correlation between samples of the same person  ...  In this paper we introduce a method to overcome one of the main challenges of person re-identification in multi-camera networks, namely cross-view appearance changes.  ...  In particular we provide a side-byside comparison of the proposed multi-channel, multi-kernel KCCA (MCK-CCA) with recent state-of-the-art techniques such as: EIML [9] , RPLM [30] , eSDC [15] , KLMM  ... 
doi:10.1145/3038916 fatcat:snxut4romfazflo27dea3a7pca

MOROCO: The Moldavian and Romanian Dialectal Corpus

Andrei Butnaru, Radu Tudor Ionescu
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
We perform experiments using a shallow approach based on string kernels, as well as a novel deep approach based on character-level convolutional neural networks containing Squeeze-and-Excitation blocks  ...  This allows us to perform empirical studies on several classification tasks such as (i) binary discrimination of Moldavian versus Romanian text samples, (ii) intra-dialect multi-class categorization by  ...  Acknowledgments We thank reviewers for their useful comments.  ... 
doi:10.18653/v1/p19-1068 dblp:conf/acl/ButnaruI19 fatcat:76dmf2o5rbftpmjj6tqvci43da

MOROCO: The Moldavian and Romanian Dialectal Corpus [article]

Andrei M. Butnaru, Radu Tudor Ionescu
2019 arXiv   pre-print
We perform experiments using a shallow approach based on string kernels, as well as a novel deep approach based on character-level convolutional neural networks containing Squeeze-and-Excitation blocks  ...  This allows us to perform empirical studies on several classification tasks such as (i) binary discrimination of Moldavian versus Romanian text samples, (ii) intra-dialect multi-class categorization by  ...  In order to understand why the KRR based on the presence bits string kernel works so well in In a similar manner, we look at examples of features weighted as discriminative by the KRR based on the presence  ... 
arXiv:1901.06543v2 fatcat:i45hq4rcpndajh5blabr2bv324

Cross-Correlation Based Discriminant Criterion for Channel Selection in Motor Imagery BCI Systems [article]

Jianli Yu, Zhuliang Yu
2021 arXiv   pre-print
Many electroencephalogram (EEG)-based brain-computer interface (BCI) systems use a large amount of channels for higher performance, which is time-consuming to set up and inconvenient for practical applications  ...  In this article, we proposed a cross-correlation based discriminant criterion (XCDC) which assesses the importance of a channel for discriminating the mental states of different motor imagery (MI) tasks  ...  The authors are with the College of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China.  ... 
arXiv:2012.01749v5 fatcat:xflkbmzbfbhefkjdgr6rhfw4za

Lower Dimensional Kernels for Video Discriminators [article]

Emmanuel Kahembwe, Subramanian Ramamoorthy
2019 arXiv   pre-print
This work presents an analysis of the discriminators used in Generative Adversarial Networks (GANs) for Video.  ...  We also show that this curvature becomes more extreme as the maximal kernel dimension of video discriminators increases.  ...  We find that the dimensionality of the 3D kernels used in video discriminators induces higher curvature in the loss landscape and that this is detrimental to first order optimization methods such as stochastic  ... 
arXiv:1912.08860v1 fatcat:aiydgshoobe3ri6y53lpd2dsr4

Multi-scale Local Difference Directional Number Pattern for Group-housed Pigs Recognition

2021 KSII Transactions on Internet and Information Systems  
Firstly, the color images of individual pig are converted into grey images by the most significant bits (MSB) quantization, which makes the grey values have better discrimination.  ...  In this paper, a multi-scale local difference directional number (MLDDN) pattern is proposed for pig identification.  ...  It is conducive to distinguishing pigs of different colours and produces compact features. (2) In order to extract more useful information and enhance the discriminative of feature descriptor, the filtering  ... 
doi:10.3837/tiis.2021.09.006 fatcat:cqyyfzquhjaz3fevxjzzntjs6m

Image-based Discrimination and Spatial Non-uniformity Analysis of Effect Coatings

Jiří Filip, Radomír Vávra, Frank Maile, Bill Eibon
2019 Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods  
Finally, we show an application of our method to analysis of spatial non-uniformity, i.e. cloudiness or mottling, across a coated panel.  ...  Our analysis has shown that the proposed method is able to clearly distinguish pigment materials and coating applications in both in-plane and out-of-plane geometries.  ...  By analysis of coverage one can observe that near 20 • aspecular (light elevation angle 25 • ) is a promising candidate for coatings discrimination (shown as angular range denoted as A); however, it should  ... 
doi:10.5220/0007413906830690 dblp:conf/icpram/FilipVME19 fatcat:2dslv5b3nvbu5noe77tjtggaam

Recent Advancements in Signal Processing and Machine Learning

Gelan Yang, Su-Qun Cao, Yue Wu
2014 Mathematical Problems in Engineering  
Liu et al. proposes a novel tensorial kernel principal component analysis (TKPCA) for feature extraction from action objects, which extends the conventional principal component analysis (PCA) in two perspectives  ...  "A virtual channels scheduling algorithm with broad applicability based on movable boundary" by Y. Tian et al. presents a novel algorithm for virtual channel scheduling based on movable boundary.  ...  Gelan Yang acknowledges the support by Scientific Research Fund of Hunan Provincial Education Department (Grant no. 12B023).  ... 
doi:10.1155/2014/549024 fatcat:aonsmhahfnaa3g3kzpvjpjuhau

Transformation-based Adversarial Video Prediction on Large-Scale Data [article]

Pauline Luc, Aidan Clark, Sander Dieleman, Diego de Las Casas, Yotam Doron, Albin Cassirer, Karen Simonyan
2021 arXiv   pre-print
We first improve the state of the art by performing a systematic empirical study of discriminator decompositions and proposing an architecture that yields faster convergence and higher performance than  ...  In this work, we focus on the task of video prediction, where given a sequence of frames extracted from a video, the goal is to generate a plausible future sequence.  ...  The network predicting these kernels, denoted by "Kernel CNN", employs a channel-wise softmax operation along the input channel to increase sparsity of the predicted kernels.  ... 
arXiv:2003.04035v3 fatcat:3zo4czcf65hwfml7r435umjm7i

Spectra Recognition Model for O-type Stars Based on Data Augmentation

Wen-Yu Yang, Ke-Fei Wu, Ke-Fei Wu, A-Li Luo, A-Li Luo, Zhi-Qiang Zou, Zhi-Qiang Zou
2021 Frontiers in Astronomy and Space Sciences  
for further analysis of astronomical spectra.  ...  To evaluate the performance of proposed models, we conducted a comparative experiment using a stellar spectral data set, which consists of more than 40,000 spectra, collected by the large sky area multi-object  ...  Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences.  ... 
doi:10.3389/fspas.2021.634328 doaj:773d0a6ec5d34f9f98ea43e62e279641 fatcat:4l6glcilija2dadoojwkhmglra

Deep Learning with Persistent Homology for Orbital Angular Momentum (OAM) Decoding [article]

Soheil Rostami, Walid Saad, Choong Seon Hong
2019 arXiv   pre-print
A Gaussian kernel with learnable parameters is proposed in order to connect persistent homology to CNN, allowing the system to extract and distinguish robust and unique topological features for the OAM  ...  Orbital angular momentum (OAM)-encoding has recently emerged as an effective approach for increasing the channel capacity of free-space optical communications.  ...  Next, we propose a novel framework that employs persistent homology as an input layer for CNN in order to probe topological features of OAM modes and enhance the OAM receiver performance. III.  ... 
arXiv:1911.06858v1 fatcat:xsjcpr42nrem3dl6yife3twtri

Cross-Correlation Aided Ensemble of Classifiers for BCI Oriented EEG Study

Parnika N. Paranjape, Meera M. Dhabu, Parag S. Deshpande, Akshay M. Kekre
2019 IEEE Access  
In this paper, we propose a two-phase approach to distinguish EEG signals of different mental tasks.  ...  The second phase performs a classification of these feature vectors using SVM and KNN classifiers.  ...  The work proposed in this paper introduced a novel two-phase approach to distinguish the up and down cursor imagery movements of a healthy subject.  ... 
doi:10.1109/access.2019.2892492 fatcat:vjl67zglhfhwjinqjuj4dfev7a
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