Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Motion vectors of depth-maps in multiview and free-viewpoint videos exhibit strong spatial as well as inter-component clustering tendency. This paper presents a novel coding technique that first compresses the multidimensional bitmaps of macroblock mode and then encodes only the non-zero components of motion vectors. The bitmaps are partitioned into disjoint cuboids using binary tree based decomposition...
Variations of target appearances due to illumination changes, heavy occlusions and abrupt motions are the major factors for tracking failures. In this paper, we show that these failures can be effectively handled by exploiting the trajectory consistency between the current tracker and its historical trained snapshots. Here, we propose a Scale-adaptive Multi-Expert (SME) tracker, which combines the...
The paper presents an approach for feature selection in human activity recognition. Features are extracted based on spatiotemporal orientation energy and activity template, while feature reduction has been studied thoroughly using various techniques. Due to high dimensional data from extraction phase, a model with less features which are important and significant can build attractive, interpretative...
Recommendation is an important problem in the traditional field of data mining. As a consequence, various kinds of algorithms have been proposed in the last few years to improve the recommendation performance. However, many of them overlook users' rating behaviors. In this paper, an improved recommendation algorithm with considering users' habits and rating behaviors will be proposed. Firstly, calculate...
Over past few decades, frog species have been experiencing dramatic decline around the world. The reason for this decline includes habitat loss, invasive species, climate change and so on. To better know the status of frog species, classifying frogs has become increasingly important. In this study, acoustic features are investigated for multi-level classification of Australian frogs: family, genus...
Canonical correlation analysis (CCA) is an established multi-variate statistical method for finding similarities between linear combinations of (normally two) sets of multivariate observations. In this contribution we replace (linear) correlation as the measure of association between the linear combinations with the information theoretical measure mutual information (MI). We term this type of analysis...
Correlations between L-band SAR polarimetric parameters obtained with airborne SAR (Pi-SAR-L2) and metrics obtained with airborne LiDAR were examined to identify the relationship between the full polarimetric parameters and forest parameters obtained for a natural forest in Indonesia. Values of a0HV and a0VV show good correlations with canopy height and 90th percentile metrics of LiDAR, with R2 values...
In general we categorize all malicious codes that potentially can harm a single or network of computers into malware groups. With great progress in enhancing virus development kit and various kind of malware appeared today, and increasing in number of web networks users, malwares spreading out rapidly in all aspect of computers systems. The main approach for finding and detecting malware today, is...
This paper presents a fuzzy fusion technique for multimodal medical image fusion using type-2 fuzzy set and near set. For each pixel of both source images, pixel-wise fuzzification based on histogram level is done. Then, construct type-2 fuzzy membership grade from both fuzzified images to quantify the uncertainty of shape of membership function. Later, fuzzy entropy, mutual information and correlation...
The electrical activity of the brain can be studied thoroughly through the recordings of the Electroencephalography (EEG) signals and is considered as a vital tool for the analysis and diagnosis of neurological diseases like tumours of the brain, epilepsy and other cognitive disorders. Due to the continuous electrical discharges from the cortex of the cerebrum, epilepsy occurs which results in several...
By using fractal dimension and sample entropy, we investigated the complexity electroencephalogram (EEG) during an activity that uses working memory. We conduct a short-term memory test and a calculation task and analyzed 1.0s EEG data from 4 phases (resting, encoding, retrieval and calculation phase). As a result, fractal dimension analysis can reflect the activity of the working memory better than...
Clustering explores meaningful patterns in the non-labeled data sets. Cluster Ensemble Selection (CES) is a new approach, which can combine individual clustering results for increasing the performance of the final results. Although CES can achieve better final results in comparison with individual clustering algorithms and cluster ensemble methods, its performance can be dramatically affected by its...
It is now known that multiscale entropy has the potential to distinguish certain pathological time series clearly and reliably from the corresponding healthy series. However, the implications of this parameter for Heart Rate Variability (HRV) have not been studied extensively. Also, as reported by other studies, the Poincare plots of the R-R interval series of a human subject's ECG signal (which too...
In order to provide good service and improve user's feeling and degree of satisfaction, video service providers are now interested in understanding the influence of attributes on Quality of Experience (QoE). In this paper, based on IPTV business, we study the relationship between alarming data from IPTV set-top boxes and the user's QoE. First, data cleaning and analysis are performed. After these...
Protein-protein interaction (PPI) networks are valuable biological data source which contain rich information useful for protein function prediction. The PPI network data set obtained from high-throughput experiments is known to be noisy and incomplete. By modeling PPI data as a graph, research efforts are being made in the literature to improve the performance of protein function prediction by extending...
We introduce and construct a pseudorandom object which we call a local correlation breaker (LCB). Informally speaking, an LCB is a function that gets as input a sequence of r (arbitrarily correlated) random variables and an independent weak-source. The output of the LCB is a sequence of r random variables with the following property. If the i'th input random variable is uniform then the i'th output...
Scanning X-ray microdiffraction (SXMD) is a novel technique to study the macromolecular architecture of tissues, such as cellulose in biomass. SXMD can generate huge amount of scattering patterns corresponding to different positions on a sample. In this paper, 190 images in a 38 × 5 grid are collected from SXMD experiment done at APS in Argonne National Lab to study nanoscale architecture in plant...
In this paper, we propose an activity-enhanced load forecasting model at house-level. We focus on the impact of residents' daily activities on entire household's power consumption. The contribution of this paper is 3-fold: 1) a web-based system for collecting daily activity information in diary-style; 2) a correlation analysis between activities and power consumption and their information-theoretic...
It is shown that large neural networks allow solving tasks that cannot classical quadratic forms in linear algebra. Thus the assessment of output entropy of neural network converters biometrics code is possible. The assessment of high-dimensional entropy is based on the symmetrization of the problem of the correlation of biometric data. Entropy of low dimension and high-dimensional entropy are differently...
Data quality is a challenging problem in many real world application domains. While a lot of attention has been given to detect anomalies for data at rest, detecting anomalies for streaming applications still largely remains an open problem. For applications involving several data streams, the challenge of detecting anomalies has become harder over time, as data can dynamically evolve in subtle ways...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.