This article investigates efficient blind watermark decoding approaches for hidden messages embedded into host images, within the framework of additive spread spectrum (SS) embedding based for data hiding. We study SS embedding in both the discrete cosine transform and the discrete Fourier transform (DFT) domains. The contributions of this article are multiple-fold: first, we show that the conv...

So far, various components of image characteristics have been used for steganalysis, including the histogram characteristic function, adjacent colors distribution, and sample pair analysis. However, some certain steganography methods have been proposed that can thwart some analysis approaches through managing the embedding patterns. In this regard, the present paper is intended to introduce a n...

Recent years have seen a growing number of graph-based semisupervised learning methods. While the literature currently contains several of these methods, their relationships with one another and with other graph-based data analysis algorithms remain unclear. In this paper, we present a unified view of graph-based semi-supervised learning. Our framework unifies three important and seemingly unre...

Network embedding methods have garnered increasing aŠention because of their e‚ectiveness in various information retrieval tasks. Œe goal is to learn low-dimensional representations of vertexes in an information network and simultaneously capture and preserve the network structure. Critical to the performance of a network embedding method is how the edges/vertexes of the network is sampled for ...

Graph embedding techniques are useful to characterize spectral signature relations for hyperspectral images. However, such images consists of disjoint classes due to spatial details that are often ignored by existing graph computing tools. Robust parameter estimation is a challenge for kernel functions that compute such graphs. Finding a corresponding high quality coordinate system to map signa...

Visualization methods that arrange data objects in 2D or 3D layouts have followed two main schools, methods oriented for graph layout and methods oriented for vectorial embedding. We show the two previously separate approaches are tied by an optimization equivalence, making it possible to relate methods from the two approaches and to build new methods that take the best of both worlds. In detai...

In this paper, we propose the concept of Manifold of Facial Expression based on the observation that images of a subject’s facial expressions define a smooth manifold in the high dimensional image space. Such a manifold representation can provide a unified framework for facial expression analysis. We first apply Active Wavelet Networks (AWN) on the image sequences for facial feature localizatio...

‎For a given measure space $(X,{mathscr B},mu)$ we construct all measure spaces $(Y,{mathscr C},lambda)$ in which $(X,{mathscr B},mu)$ is embeddable‎. ‎The construction is modeled on the ultrafilter construction of the Stone--v{C}ech compactification of a completely regular topological space‎. ‎Under certain conditions the construction simplifies‎. ‎Examples are given when this simplification o...

Abstract Generalized parallelizable spaces permit the uplift of many maximal gauged supergravities to ten or eleven dimensions. Although some former are explicitly known, literature is still lacking their systematic construction. We resolve this issue by going beyond known existence proofs and present explicit construction all generalized for in four more In process, embedding tensors that can ...

We study the normal bundles of exceptional sets isolated simple small singularities in higher dimension when Picard group set is $\mathbb{Z}$ and bundle it has some good filtration. In particular, for a projective space with split bundle, we generalized Nakayama Ando's results to dimension. Moreover, also generalize Laufer's rationality embedding