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A systematic analytical procedure based on the concept of the analytic signal (AS) of Gabor is used to estimate amplitude and phase of input multi-harmonic signal. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), the reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick...
Recognition of epileptic seizures is an important issue and in certain circumstances it is desirable to have portable equipment implementing the algorithm in order to better monitor the patients. This work considers a widely used EEG database from University of Bonn as reference for comparing our recognition method with other previously reported. In order to perform epileptic seizures we combine a...
This documents presents a development methodology which purpose is propose procedures that allows to transform a monolithic system into an architecture based in microservices the document offers a description of each stage and explains it's implementation of the methodology in an open source monolith application. The methodology starts from the analysis of the business model of a monolithic application...
Pathological high-frequency oscillations (HFOs, 200–600 Hz) observed in depth-EEG and on scalp EEG recordings are recognized to be potentially valuable biomarkers of the epileptogenic zone responsible for generating seizures. Many research studies have been dedicated to detect, classify, simulate and understand the underlying mechanisms responsible for their generation. However, broadly classifying...
Traversable region estimation is the fundamental enabler in autonomous navigation. In this paper, we propose a traversable region segmentation algorithm using stereo vision. We address this problem mainly in road scenes for the goal of autonomous driving. Using only geometry information, our approach has the advantages of effectiveness and robustness. The proposed approach is based on a cascaded framework...
In this paper, a slack variable-based control variable parameterization (CVP) method is proposed for solving engineering dynamic optimization problems with inequality path constraints. An improved slack variable transform technique is introduced so that the original problem is converted into an unconstrained dynamic optimization problem (uDOP). No approximation error generated and the inequality path...
The paper presents the reasonable environment cognition model for multifunction phased array radar based on time-frequency analysis and high order spectra analysis. At first, typical radar waveforms for different functions are introduced. Aim to extract the signal modulation characteristics corresponding to special radar task, the WVD-Hough transform and Bispectrum estimation are proposed. The WVD-Hough...
Convolutional Neural Network (CNN) has led to significant progress in face recognition. Currently most CNNbased face recognition methods follow a two-step pipeline, i.e. a detected face is first aligned to a canonical one predefined by a mean face shape, and then it is fed into a CNN to extract features for recognition. The alignment step transforms all faces to the same shape, which can cause loss...
We introduce Appearance-MAT (AMAT), a generalization of the medial axis transform for natural images, that is framed as a weighted geometric set cover problem. We make the following contributions: i) we extend previous medial point detection methods for color images, by associating each medial point with a local scale; ii) inspired by the invertibility property of the binary MAT, we also associate...
Spectral signatures of natural scenes were earlier found to be distinctive for different scene types with varying spatial envelope properties such as openness, naturalness, ruggedness, and symmetry. Recently, such handcrafted features have been outclassed by deep learning based representations. This paper proposes a novel spectral description of convolution features, implemented efficiently as a unitary...
Humans take advantage of real world symmetries for various tasks, yet capturing their superb symmetry perception mechanism with a computational model remains elusive. Motivated by a new study demonstrating the extremely high inter-person accuracy of human perceived symmetries in the wild, we have constructed the first deeplearning neural network for reflection and rotation symmetry detection (Sym-NET),...
Compressed sensing (CS) is a signal processing framework for efficiently reconstructing a signal from a small number of measurements, obtained by linear projections of the signal. Block-based CS is a lightweight CS approach that is mostly suitable for processing very high-dimensional images and videos: it operates on local patches, employs a low-complexity reconstruction operator and requires significantly...
Although there has been increasing demand for more reliable web applications, JavaScript bugs abound in web applications. In response to this issue, researchers have proposed automated fault detection tools, which statically analyze the web application code to find bugs. While useful, these tools either only target a limited set of bugs based on predefined rules, or they do not detect bugs caused...
Smart objects (SOs) have been utilized widely to transform the physical environment around us to a digital world using the Internet of things (IoT) vision. Integrating a huge number of these devices into the Internet presents a significant necessity for an efficient discovery mechanism with high capability of an autonomous configuration and detection for theses devices and their provided services...
We propose a signal-channel, adaptive threshold selection technique for binary mask construction, namely APHONIC, (AdaPtive tHreshOlding for NoIse Cancellation) for smart mobile environments. Using this mask, we introduce two noise cancellation techniques that perform robustly in the presence of real-world interfering signals that are typically encountered by mobile users: a violin busker, a subway...
The increasing demand of aviation electrification makes the detection of arc faults for AC Solid State Power Controller (SSPC) in more electric aircraft (MEA) imminent, since it has to be done while SSPC is still in operation and such arc faults will not provide considerable fault features. In this paper, a method based on Hilbert-Huang transform (HHT) and amplitude threshold detection is proposed...
Automatic parking systems have significant effects on intelligent transport systems (ITS) and have been extensively researched. However, most existing vision-based automatic parking slot detection methods cannot obtain the desired results due to variation in light intensity or complex obstacle conditions. Besides, most previous parking slot detection methods only consider the target position occupied...
Advances in virtual reality have generated substantial interest in accurately reproducing and storing spatial audio in the higher order ambisonics (HOA) representation, given its rendering flexibility. Recent standardization for HOA compression adopted a framework wherein HOA data are decomposed into principal components that are then encoded by standard audio coding, i.e., frequency domain quantization...
Interest on palmprint biometrics has experimented a strong growth in the last decades due to its useful characteristics as uniqueness, permanence, reliability, user-friendliness, acceptability, non-intrusiveness, and low cost of the acquisition devices, which make it attractive for civil and commercial applications. Accordingly, a wide research has been developed in this field. Nevertheless, there...
Automated segmentation of cell nuclei is crucial for the early diagnosis of cancer as the characteristics of the cell nuclei are mainly associated with the assessment of malignancy. Only a few research work has been done on automated segmentation of cell nuclei on cytology pleural effusion images, which is poorly handled by previous methods. In addition, cytology pleural effusion image itself is still...
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