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.
Recent studies have indicated that well-designed convolutional neural network (CNN) has achieved comparable performance to the spatial rich models with ensemble classifier (SRM-EC) in digital image steganalysis. In this paper, we discuss the difference and correlation between a CNN model and a SRM-EC model, and explore the classification error rate varying with texture complexity of an image for both...
In this paper, we address the problem of conditional modality learning, whereby one is interested in generating one modality given the other. While it is straightforward to learn a joint distribution over multiple modalities using a deep multi-modal architecture, we observe that such models are not very effective at conditional generation. Hence, we address the problem by learning conditional distributions...
Object tracking is an important capability for robots tasked with interacting with humans and the environment, and it enables robots to manipulate objects. In object tracking, selecting samples to learn a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and frequency of model updating, which concerns many details that can affect the tracking...
Building large-scale 2.5D maps when spatial correlations are considered can be quite expensive, but there are clear advantages when fusing data. While optimal submapping strategies have been explored previously in covariance-form using Gaussian Process for large-scale mapping, this paper focuses on transferring such concepts into information form. By exploiting the conditional independence property...
Sleep is a dynamic process which can be described by a finite set of sleep stages. In contrast to the standard discrete Rechtschaffen and Kales sleep model continuous sleep representation provided by the Probabilistic Sleep Model allows to take into account the whole dynamic of the sleep process. However, analysis of the sleep probabilistic curves faces problems when the time misalignment is present...
Large-Eddy Simulations (LES) of an array of wind turbines have been carried out to design and evaluate a model-free approach, extremum-seeking control (ESC), for power maximization. This paper shows how to coordinate the action of the extremum seeking controllers (at each turbine) by nesting the objective functions used for optimization so that the power of the overall array is maximized. The paper...
Heterogeneous data sources and multi-label are two important characteristics of protein function prediction. They describe protein data from two different aspects. However, it is of considerable challenge to integrate multiple data sources and multi-label simultaneously for predicting protein functions, especially when there are only a limited number of labeled proteins. In this paper, we propose...
This study provided a method to simulate flow field of an irregular arrangement of random packing in an absorber using commercial software, Fluent®. Volume of fluid model was employed in this study to deal with gas and liquid phases contacting issue. Volume of fluid model has validated that it is able to simulate gas and liquid interface. 10 flow fields of small-scale absorbers in which several raschig...
In recent years, the correlation filter-based trackers (CFTs) have shown to provide excellent results in different competitions and benchmarks, but there is still a need to improve the robustness of CFTs. Compared with the traditional kernel correlation filter tracker, the approach we present in this paper makes some significant improvements. The strong features including HOG and Color-naming are...
This paper aims to propose and discuss concepts of how users can recognise information seeking behaviour automatically and what implications such an automatic recognition can have. The authors develop the discussion around variables proposed in Wilson's second model of information behaviour and state how they can collect data necessary to recognise information behaviour automatically. The authors...
Text categorization, or text classification, is one of key tasks for representing the semantic information of documents. Multi-label text categorization is finer-grained approach to text categorization which consists of assigning multiple target labels to documents. It is more challenging compared to the task of multi-class text categorization due to the exponential growth of label combinations. Existing...
Clinicians are interested in the estimation of robust and relevant genetic signatures from gene sequencing data. Many machine learning approaches have been proposed trying to address well-known issues of this complex task (feature or gene selection, classification or model selection, and prediction assessment). Addressing this problem often requires a deep knowledge of these methods and some of them...
Recent advances in neuroscience made it possible to understand how the human brain processes emotions and affective states. However, the modeling of emotion remains elusive due to inherent ambiguity and complexity related to the perception of emotions, interpersonal variabilities, and context-specific interpretations. Here, we present a robust method of modeling 4-D continuous affective space (Valence,...
It is common practice to discretize continuous defect counts into defective and non-defective classes and use them as a target variable when building defect classifiers (discretized classifiers). However, this discretization of continuous defect counts leads to information loss that might affect the performance and interpretation of defect classifiers. Another possible approach to build defect classifiers...
We present a holistic segmentation-free query by example word spotting technique based on template matching. We have applied this technique to a dataset of historical Arabic handwritten manuscript images. First, the documents as well as query word images are pre-processed for separating text from the noisy background and converting to their binary equivalents. Then a pixel based approach is used for...
This paper presents our study results on the correlated assignment of generation, load, or connection buses in a given grid topology and the development of an optimized search algorithm to improve the proposed synthetic grid model, called RT-nestedSmallWorld. A numerical measure, called “Bus Type Entropy”, was proposed in an initial study on this subject to characterize the correlation of bus type...
Differential power analysis (DPA) is one of the most common side channel attacks. To perform this attack we need to calculate a large amount of correlation coefficients. This amount is even higher when attacking FPGAs or ASICs, for higher order attacks and especially for attacking DPA protected devices. This article explains different approaches to the calculation of correlations, describes our implementation...
Recent work proposes new algorithms for feature selection based on a Bayesian hierarchical model that places priors on both the identity of all features, and the identity-conditioned feature-label distribution. Given training data, Bayesian inference can be used to predict the feature identities. While algorithms developed in prior work rely on certain independence assumptions, in this work we present...
Robust appearance model is significantly important to state-of-the-art trackers. However, such trackers highly rely on the reliability of foreground appearance model. When the foreground is seriously occluded or the scene contains multiple objects with similar appearance, such foundation is destroyed. To extend the ability of trackers to handle these difficulties, we propose selective object and context...
When distances between microphone pairs are larger than the half-wavelength of signals, source localization methods using cross-correlation such as time-difference-of-arrival (TDOA), steered response power (SRP) are commonly used in practice. We present here a novel model that expresses microphone pairwise cross-correlations as a sum of autocorrelations of source signals shifted by the relative delays...
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.