The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The success of fine-grained visual categorization (FGVC) extremely relies on the modeling of appearance and interactions of various semantic parts. This makes FGVC very challenging because: (i) part annotation and detection require expert guidance and are very expensive; (ii) parts are of different sizes; and (iii) the part interactions are complex and of higher-order. To address these issues, we...
With the bottom-line goal of increasing the throughput of a GPU-accelerated JPEG 2000 encoder, this paper evaluates whether the post-compression rate control and packetization routines should be carried out on the CPU or on the GPU. Three co-processing models that differ in how the workload is split among the CPU and GPU are introduced. Both routines are discussed and algorithms for executing them...
Sparse Modeling Representative Selection (SMRS) has been recently proposed for finding the most relevant instances in datasets. This method deploys a data self-representativeness coding in order to infer a coding matrix that is regularized with a row sparsity constraint. The method assumes that the score of any sample is set to the L2 norm of the corresponding row in the coding matrix. Since the SMRS...
Interactive video streaming requires very low latency and high throughput. Traditional latency based congestion control algorithm performs poorly in fairness. This results in very poor video quality to adaptive video streaming. Software defined networks (SDN) enables us to solve the problem by designing a network controller in the routers. This paper presents a SDN-centric TCP where sending rate of...
Most recent CNN architectures use average pooling as a final feature encoding step. In the field of fine-grained recognition, however, recent global representations like bilinear pooling offer improved performance. In this paper, we generalize average and bilinear pooling to “α-pooling”, allowing for learning the pooling strategy during training. In addition, we present a novel way to visualize decisions...
Ste gano graphic systems are used for the transmission of hidden data in the original signal. The article describes the algorithm of the hidden data transmission using the speech signal as a carrier. The echo method is used for data embedding. In order to improve the decoding efficiency of embedded data, the procedure of voicing correction and mechanism of informed coding were developed and implemented...
This paper aims to develop an effective flower classification approach using the technology of feature extraction. With this regard, a fused descriptor based on Pyramid Histogram of Visual Words (PHOW) is used to extract the color, texture and contour information of flower image. Secondly, Dictionary Learning and Locality-constrained Linear Coding (LLC) are operated on PHOW feature and then images...
Multiple transforms have received considerable attention recently, especially in the course of an exploration conducted by MPEG and ITU toward the standardization of the next generation video compression algorithm. This joint team has developed a software, called the Joint Exploration Model (JEM) which outperforms by over 25% the HEVC standard. The transform step in JEM consists in Adaptive Multiple...
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...
Classification of multisensor data provides potential advantages over a single sensor in accuracy. In this paper, deep bimodal autoencoders are proposed for classification of fusing synthetic aperture radar (SAR) and multispectral images. The proposed deep network based on autoencoders is trained to discover both independencies of each modality and correlations across the modalities. Specifically,...
This paper presents the design of a new hardware accelerator, filtering the input data using Gabor functions and dedicated to image processing. The proposed design obtains a great reduction in terms of resources if compared to other state-of-the-art implementations. This is done exploiting the separability of Gabor filters along certain orientations and through a reorganization of the arithmetic units...
The High Efficiency Video Coding (HEVC) standard significantly saves coding bit-rate over the proceeding H.264 standard, but at the expense of extremely high encoding complexity. In fact, the coding tree unit (CTU) partition consumes a large proportion of HEVC encoding complexity, due to the brute-force search for rate-distortion optimization (RDO). Therefore, we propose in this paper a complexity...
Rise in wireless data traffics requires innovative interference management techniques to meet the demand. Transmit cooperation among multiple base stations has been proposed as a solution to this challenge and improve throughput. For base stations equipped with massive MIMO arrays, a proposed subspace encoding technique can decouple the joint multicell resource allocation problems into independent...
It is well recognized that the signal processing methods contributes in biology to the control of the DNA spatial structure. From the previous studies, it is inferred that the significant portion of the eukaryotic genomes is composed of transposable elements (TEs). The TEs play an important role as a driving force of genome evolution. An important sub class of ETs class II, Helitrons, have been revealed...
Restrict Boltzmann Machine, a generative model that consists of one visible layer and one hidden layer, plays an important role in deep learning. It can be used as a feature extractor in an unsupervised way. In process diagnosis area, the Sparse Class Gaussian Restrict Boltzmann Machine is developed as a discriminative nonlinear feature extractor for classification in order to solve the discriminative...
In order to improve the detection performance of the main symmetry axis, a new detection method based on the clustering analysis is proposed. Some feature points are extracted from the image based on the Harris corner detection, and C-means clustering method is used to classify the feature points into C groups. Multiple random sampling is performed in each cluster to get the feature point pairs. The...
In this paper, we exploit the intrinsic relation between different adjective labels and develop a novel multilabel dictionary learning and sparse coding method which is improved by introducing the structured output association information. Such a method makes use of the label correlation information and is more suitable for the multi-label tactile understanding task. In addition, we develop a globally-convergent...
Today, machine learning based on neural networks has become mainstream, in many application domains. A small subset of machine learning algorithms, called Convolutional Neural Networks (CNN), are considered as state-ofthe- art for many applications (e.g. video/audio classification). The main challenge in implementing the CNNs, in embedded systems, is their large computation, memory, and bandwidth...
As the analytic tools become more powerful, and more data are generated on a daily basis, the issue of data privacy arises. This leads to the study of the design of privacy-preserving machine learning algorithms. Given two objectives, namely, utility maximization and privacy-loss minimization, this work is based on two previously non-intersecting regimes — Compressive Privacy and multi-kernel method...
The problem of deterministieally coding a continuous time signal using an ensemble of spike trains is addressed. Coding is defined with an eye toward “efficiency”, defined as a trade-off between the number of spikes in the code and the quality of the code operationalized using the notion of reconstruction error. It is shown that inverting the coding model leads to a reconstruction procedure that amounts...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.