In this paper a novel technique for Neighbor embedding single image super resolution (SR) is proposed. Given a low-resolution image, its highresolution image is reconstructed from a set of training images, which are composed of one or more lowresolution and corresponding high-resolution image pairs. In this paper we propose a new approach to a single image super-resolution through neighbor embe...

In this paper, we develop a novel approach to aspect term extraction based on unsupervised learning of distributed representations of words and dependency paths. The basic idea is to connect two words (w1 and w2) with the dependency path (r) between them in the embedding space. Specifically, our method optimizes the objective w1 + r ≈ w2 in the low-dimensional space, where the multihop dependen...

Recently, Wang et al. [1] proposed a new method for constructing pairingfriendly elliptic curves of embedding degree 1. Authors claim that this method significantly improves the efficiency of generating elliptic curves. In this paper, we give the arithmetic of pairing-friendly elliptic curves of embedding degree 1. We prove that conventional classification of pairings into Type 1, 2, 3 and 4 is...

A novel adaptive steganographic scheme for spatial image is proposed. A noisy function is used to measure texture complexity of 2 × 2 pixel blocks, which keeps monotonic increasing after ±1 modifications. Therefore, the message is embedded into the noisiest areas and the recipient can identify the embedding region. The ‘double-layered embedding’ is exploited to reduce the number of ±1 modificat...

UNLABELLED PREMISE OF THE STUDY Bacterial contamination is a major problem in plant tissue culture, resulting in loss of experimental strains or preventing use of field-collected isolates. Here we evaluated an agar embedding method for eliminating bacteria from experimental cultures of the mosses Ceratodon purpureus and Physcomitrella patens. • METHODS AND RESULTS We blended moss protonema...

This letter deals with the de-embedding of on-wafer CMOS FETs embedded in symmetrical and reciprocals pads. A de-embedding method, that uses a calibrated vector network analyzer and two microstrip lines fabricated on a lossy SiO2-Si substrate, is introduced. The proposed method not only allows the characterization on the interconnection lines but also allows the characterization of the CMOS pad...

Digital images are increasingly being used as steganographic covers for secret communication. The Least Significant Bit (LSB) encoding is one of the most widely used methods for embedding a message in a digital image. However, the direct application of LSB encoding is vulnerable to steganalysis. For example, RS steganalysis is very efficient in detecting the presence of a message in a digital i...

In this paper, we propose a novel method for image feature extraction, namely the twodimensional local graph embedding, which is based on maximum margin criterion and thus not necessary to convert the image matrix into high-dimensional image vector and directly avoid computing the inverse matrix in the discriminant criterion. This method directly learns the optimal projective vectors from 2D im...

High embedding capacity and low image distortion factors are main concerns of information hiding researchers. No scheme can achieve these two factors simultaneously. The purpose of achieving either high embedding capacity or low image distortion varies from application to application. This paper presents a high embedding capacity information hiding method for grayscale images. The proposed meth...

Concept-based representation — combined with some classifier (e.g., support vector machine) or regression analysis (e.g., linear regression) — induces a popular approach among image processing community, used to infer image labels. We propose a supervised learning procedure to obtain an embedding to a latent concept space with the pre-defined inner product. This learning procedure uses rank min...