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In this paper, we propose a new discriminative dictionary learning framework, called robust Label Embedding Projective Dictionary Learning (LE-PDL), for data classification. LE-PDL can learn a discriminative dictionary and the blockdiagonal representations without using the l0-norm or l1-norm sparsity regularization, since the l0 or l1-norm constraint on the coding coefficients used in the existing...
Current light field compression techniques lack robustness to handle both rate-distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced frame prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance...
Audio Steganography is the technique of hiding any secret information behind a cover audio file without impairing its quality. Data hiding in audio signals has various applications such as secret communications and concealing data that may influence the security and safety of governments and personnel and has possible important applications in 5G communication systems. This paper proposes an efficient...
Codes that aim to detect any error regardless of its multiplicity are referred to as security oriented codes. Most of these codes are designed to protect uniformly distributed codewords; there are few solutions which are used in protecting systems with non-uniformly distributed words. The paper introduces a new encoding method, termed “Level-Out encoding”, for cases in which some words are more likely...
This paper presents BIND (Binary Integrated Net Descriptor), a texture-less object detector that encodes multi-layered binary-represented nets for high precision edge-based description. Our proposed concept aligns layers of object-sized patches (nets) onto highly fragmented occlusion resistant line-segment midpoints (linelets) to encode regional information into efficient binary strings. These lightweight...
Numerous methods have been proposed for person re-identification, most of which however neglect the matching efficiency. Recently, several hashing based approaches have been developed to make re-identification more scalable for large-scale gallery sets. Despite their efficiency, these works ignore cross-camera variations, which severely deteriorate the final matching accuracy. To address the above...
Rolling element bearings play an important role in ensuring the availability of industrial machines. Unexpected bearing failures in such machines during field operation can lead to machine breakdown, which may have some pretty severe implications. However, the insufficiency of labeled samples is major problem for handling fault diagnosis problem. To address such concern, we propose a semi-supervised...
During the past decade, graph-based semi-supervised learning has become one of the most important research areas in machine learning and artificial intelligence community. In this paper, we propose a Capped l2,1-Norm Regularized Dictionary Learning to construct the graph for semi-supervised learning (SSL). The new sparse coding is robust to the outliers and insensitive to noise. Then, the developed...
The CNN-encoding of features from entire videos for the representation of human actions has rarely been addressed. Instead, CNN work has focused on approaches to fuse spatial and temporal networks, but these were typically limited to processing shorter sequences. We present a new video representation, called temporal linear encoding (TLE) and embedded inside of CNNs as a new layer, which captures...
When considering person re-identification (re-ID) as a retrieval process, re-ranking is a critical step to improve its accuracy. Yet in the re-ID community, limited effort has been devoted to re-ranking, especially those fully automatic, unsupervised solutions. In this paper, we propose a k-reciprocal encoding method to re-rank the re-ID results. Our hypothesis is that if a gallery image is similar...
Noise robustness has long garnered much interest from researchers and practitioners of the automatic speech recognition (ASR) community due to its paramount importance to the success of ASR systems. This paper presents a novel approach to improving the noise robustness of speech features, building on top of the dictionary learning paradigm. To this end, we employ the K-SVD method and its variants...
Fountain codes are used in many applications where the channels are time varying and it is difficult at the transmitter to predict the appropriate code rate. In this situation, fixedrate codes are not suitable. Despite the good performance of fountain codes, universally optimal codes do not exist in the finite-length regime. In this paper, we design new fountain codes that are robust to the communication...
We introduce Cyclone codes which are rateless erasure resilient codes. They combine Pair codes with Luby Transform (LT) codes by computing a code symbol from a random set of data symbols using bitwise XOR and cyclic shift operations. The number of data symbols is chosen according to the Robust Soliton distribution. XOR and cyclic shift operations establish a unitary commutative ring if data symbols...
A balanced code is a set of words over [a, b} such that the number of a's and the number of b's in a word are equal, and many applications using balanced codes have been proposed so far. Recently, not only the original balanced code, but also balanced codes with some other constraints have been studied mainly for an application of data storage media. However, contrary to other typical sets of words...
Minimum energy required to achieve a distortion-noise profile, i.e., a function indicating the maximum allowed distortion value for each noise level, is studied for robust transmission of Gaussian sources over Gaussian channels. It is shown that for the inversely linear profile, uncoded transmission is optimal. On the other hand, it turns out that exponential profiles are not achievable with finite...
After deeply analyzing the standard of MPEG2 video encoding formats, proposing a MPEG2 video watermarking technology based DC coefficient. The binary image is treated as watermarking information after being dealt with the mixed method of Logistic chaotic map and error correction coding. Unlike the traditional watermarking algorithm, it is not necessary to decode all the video data, and to do inverse...
Owing to the rapid growth in high-quality video streaming over the Internet, preserving high-level robustness against data loss and low latency, while maintaining higher data transmission rates, is becoming an increasingly important issue for high-quality real-time delay-sensitive streaming. In this paper, we propose a low latency, low loss streaming mechanism, L4C2, specialized for high-quality delay-sensitive...
In this paper a robust encoding scheme is proposed to improve the visual quality of HEVC decoded video when intra frames are lost along the streaming path. For this purpose, the encoding process includes frame loss simulation and subsequent error concealment, to find the most efficient method that should be used by a decoder to recover lost intra frames. In this novel scheme, each image is divided...
Nowadays, video steganography has become important in many security applications. The performance of any steganographic method ultimately relies on the imperceptibility, hiding capacity, and robustness. In the past decade, many video steganography methods have been proposed; however, the literature lacks of sufficient survey articles that discuss all techniques. This paper presents a comprehensive...
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