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Encoding spatio-temporally varying textures is challenging for standardised video encoders, with significantly more bits required for textured blocks compared to non-textured blocks. It is therefore beneficial to understand video textures in terms of both their spatio-temporal characteristics and their encoding statistics in order to optimize coding modes and performance. To this end, we examine the...
Speaker diarization systems aim to segment an audio signal into homogeneous sections with only one active speaker and answer the question "who spoke when?" We present a novel approach to speaker diarization exploiting spatial information through robust statistical modeling of Time Difference of Arrival (TDOA) estimates obtained using pairs of microphones. The TDOAs are modeled with Gaussian...
The number of extracted features for fault diagnosis in rotating machinery can grow considerably due to the large amount of available data collected from different monitored signals. Usually, feature selection or reduction are conducted through several techniques proposing a unique set of representative features for all available classes; nevertheless, in feature selection, it has been recognized...
The paper presented a systematic evaluation of the weight sparsity regularization schemes for the deep neural networks applied to the whole brain resting-state functional magnetic resonance imaging data. The weight sparsity regularization was deployed between the visible and hidden layers of the Gaussian-Bernoulli restricted Boltzmann machine (GB-RBM), in which the L0-norm based non-zero value ratio...
Image quality assessment gains a greater interest due to development of digital imaging and storage. In that field, structural similarity (SSIM) index has been shown to favorably agree with human perceptual assessment, significantly outperforming the method of mean squared error, i.e., L2 distance. The similarity measure function in SSIM which compares a target (distorted) image with its reference...
This paper presents a method for the detection of wakeful state, rapid eye movement sleep (REM), light sleep (N1&N2) and deep sleep (N3&N4) based on cardiorespiratory parameters. Experiments were conducted with data of 625 subjects without sleep-disordered breathing selected from the SHHS dataset. Compared to previous studies, our method considers results of neighboring epochs classification...
The execution logs of a business process have been recently exploited to extract classification models for discriminating “deviant” instances of the process —i.e. instances diverging from normal/desired outcomes (e.g., frauds, faults, SLA violations). Regarding all log traces as sequences of task labels, current solutions essentially map each trace onto a vector space where the features correspond...
Recently, an explicit control of weight sparsity level between the layers in the deep neural network has been proposed and gainfully been utilized to resting-state fMRI (rfMRI) data. However, the reliability of the weight sparsity control scheme via the percentage of non-zero weights (PNZ) was not systematically evaluated in term of the convergence property of the sparsity levels across various scenarios...
A preliminary study on photoplethysmogram (PPG) based biometry system is presented here. PPG is a physiological signal related to cardiac output and blood flow saturation in body. Recently it is reported that being an automatic physiological phenomenon PPG and other biosignals can be used as biometric parameters for human authentication. In this work, 12 number of features are extracted from filtered...
Biopsy remains the gold standard for the diagnosis of chronic liver diseases. However, the variability in the diagnostic between readers leads to define a method to objectively describe histologic tissue. A complete framework has been implemented to analyze images of any tissue. Based on subset selection and feature ranking approaches, a feature selection computes the most relevant subset of descriptors...
Feature location is a program comprehension activity in which a developer inspects source code to locate the classes or methods that implement a feature of interest. Many feature location techniques (FLTs) are based on text retrieval models, and in such FLTs it is typical for the models to be trained on source code snapshots. However, source code evolution leads to model obsolescence and thus to the...
Shot boundary detection (SBD) is the first step towards video indexing and content based video management. Due to availability of low cost storage media devices, and broadband data connection, digital videos are becoming widely used. However, the increasing availability of digital video has not been accompanied by an increase in its ease of accessibility. If we want to see a clip of interest, we have...
Within our approach to big data, we reduce the number of images in video footage by applying a shot detection with a keyframe extraction of single frames. This can be followed by duplicate removal and face detection processes yielding to a further data reduction. Nevertheless, additional reductions steps are necessary in order to make the data manageable (searchable) for the end user in a meaningful...
In general, popular films and screenplays follow a well defined storytelling paradigm that comprises three essential segments or acts: exposition (act I), conflict (act II) and resolution (act III). Deconstructing a movie into its narrative units can enrich semantic understanding of movies, and help in movie summarization, navigation and detection of the key events. A multimodal framework for detecting...
Static video summarization techniques aim to represent the salient content in a video by extracting a set of key-frames for presentation to the user. An efficient key-frame extraction process is thus vital for effective video summarization, browsing and indexing in content-based video retrieval systems. In this paper, a three phased approach for key-frame extraction is proposed which aims to represent...
Biopsy remains the gold standard for the diagnosis of chronic liver diseases. However, the concordance between readers is subject to variability causing an increasing need of objective tissue description methods. A complete framework has been implemented to analyze histological images from any kind of tissue. Based on the feature selection approach, it computes the most relevant subset of descriptors...
In geomagnetic aided navigation (GAN), the matching suitability of candidate matching areas (CMAs), which is an important influencing factor of matching precision, can be depicted by the geomagnetic features extracted from the geomagnetic map. Firstly, the definitions of thirteen commonly used geomagnetic features are given in detail. Then the quantitative relationship between the geomagnetic features...
A method for the automatic detection of microaneurysms (MAs) in color retinal images is proposed in this paper. The recognition of MAs is an essential step in the diagnosis and grading of diabetic retinopathy. The proposed method realizes MA detection through the analysis of directional cross-section profiles centered on the local maximum pixels of the preprocessed image. Peak detection is applied...
To the goal of multiple degree of freedom (M-DOF) prosthetic hand control by characterizing events in surface electromyograms (sEMG), a system of sEMG acquisition, detection and recognition is built. It can classify commonly used eighteen kinds of hand gestures with six channels. The dynamic cumulative sum (DCS) is applied for on-line detection. Energy changes are detected with this approach, corresponding...
Based on ArcGIS and the feature analysis for the water environment and the source identification of water environmental health risks in a typical area in the western edge of Sichuan basin-Mingshan County in Ya'an City of Sichuan Province, China, this study tested the water quality of 41 drinking water sources, applied the health risk evaluation model recommended by USEPA (U.S. Environmental Protection...
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