Search results for "RECOGNITION"
showing 10 items of 3607 documents
A Spatial Pyramidal Decomposition Method for ear representation using local dual cross patterns
2019
International audience; In recent years, several scientific works are oriented to develop optimal ear representation, for ear recognition, which is discriminant, compact, and easyto-implement to ensure the best performance in terms of accuracy, computation cost, and storage requirement. In this manner, this paper presents a novel ear representation based on texture analysis framework, which relies mainly on Dual Cross Pattern (DCP) descriptor and Spatial Pyramid Histogram (SPH) method. The features are extracted using DCP descriptor to capture the textural structure then, the SPH of horizontal ear decomposition is applied to obtain the local information. The feature vector representations o…
Optimal imaging of multi-channel EEG features based on a novel clustering technique for driver fatigue detection
2020
Abstract Fatigue may cause a decrease in mental and physical performance capacity, which is a serious safety risk for the drivers in the transportation system. Recently, various studies have demonstrated the deviations of electroencephalogram (EEG) indicators from normal vigilant state during fatigue in time and frequency domains. However, when considering spatial information, these feature descriptors are not satisfying the demand for reliable detection due to the well-known challenge of signal mixing. In this paper, we propose a novel approach based on clustering on brain networks (CBNs) to alleviate the problem to improve the performance of driver fatigue detection. The clustering algori…
Estimation of Leaf Area in Bell Pepper Plant using Image Processing techniques and Artificial Neural Networks
2021
Measurement and estimation of physical properties of plant leaves have always been considered as important requirements for monitoring and optimizing of plant growth. This study aimed at utilization of image processing and artificial intelligence techniques for non-invasive and non-destructive estimation of bell pepper leaves properties in the first month of growth. Physical properties of bell pepper plant leaves were extracted from RGB images. The algorithm makes use of gradient magnitude and watershed image. Leaf area as the most important index of growth was estimated as a function of other physical parameters including leaf length, width, perimeter etc. Using stereo imaging, the leaf di…
Prefiltering for pattern recognition using wavelet transform and neural networks
2003
Publisher Summary Neural networks are built from simple units interlinked by a set of weighted connections. Generally, these units are organized in layers. Each unit of the first layer (input layer) corresponds to a feature of a pattern that is to be analyzed. The units of the last layer (output layer) produce a decision after the propagation of information. Before feeding the computational data to neural networks, the signal must undergo a preprocessing in order to (1) define the initial transformation to represent the measured signal, (2) retain important features for class discrimination and discard that is irrelevant, and (3) reduce the volume of data to be processed, for example, data …
Hydro-Acoustic Target Detection
2014
This chapter presents an example of utilization of the discrete–time wavelet packets, which are described in Sect. 9.1, to classification of acoustic signals and detection of a target. The methodology based on wavelet packets is applied to a problem of detection of a boat of a certain type when other background noises are present. The solution is obtained via analysis of boat’s hydro-acoustic signature against an existing database of recorded and processed hydro-acoustic signals. The signals are characterized by the distribution of their energies among blocks of wavelet packet coefficients.
An Improved Forecasting Model from Satellite Imagery Based on Optimum Wavelet Bases and Adam Optimized LSTM Methods
2021
This paper proposes a new hybrid approach I-WT-LSTM (i.e., Improved Wavelet Long Short-Term Memory (LSTM) Model) for forecasting non-stationary time series (TS) from satellite imagery. The proposed approach consists of two steps: The first step aims at decomposing TS using Multi-Resolution Analysis wavelet (MRA-WT) into inter-and intra-annual components using 18 different mother wavelets (MW). Then, the energy to Shannon entropy ratio criterion is calculated to select the best MW. The second step is based on the LSTM model using Adam optimizer to predict the future. The proposed approach is tested using TS derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2001 t…
Time-Frequency behaviour of the a-wave of the human electroretinogram
2007
The electroretinogram is the record of the electrical response of the retina to a light stimulus. The two main components are the a-wave and the b-wave, the former is related to the early photoreceptoral activity. Aim of this paper is to acquire useful information about the time-frequency features of the human a-wave, by means of the wavelet analysis. This represents a proper approach in dealing with nonstationary signals. We have used the Mexican Hat as mother wavelet. The analysis, carried out for four representative values of the luminance, comprehends the frequency dependence of the variance and the skeleton. The results indicate a predominance of low frequency components, their time di…
Restricted Decontamination for the Imbalanced Training Sample Problem
2003
The problem of imbalanced training data in supervised methods is currently receiving growing attention. Imbalanced data means that one class is much more represented than the others in the training sample. It has been observed that this situation, which arises in several practical domains, may produce an important deterioration of the classification accuracy, in particular with patterns belonging to the less represented classes. In the present paper, we report experimental results that point at the convenience of correctly downsizing the majority class while simultaneously increasing the size of the minority one in order to balance both classes. This is obtained by applying a modification o…
Characterization of the human visual system threshold performance by a weighting function in the Gabor domain
1997
Abstract As evidenced by many physiological and psychophysical reports, the receptive fields of the first-stage set of mechanisms of the visual process fit to two-dimensional (2D) compactly supported harmonic functions. The application of this set of band-pass filter functions to the input signal implies that the visual system carries out some kind of conjoint space/spatial frequency transform. Assuming that a conjoint transform is carried out, we present in this paper a new characterization of the visual system performance by means of a weighting function in the conjoint domain. We have called this weighting function (in the particular case of the Gabor transform) the Gabor stimuli Sensiti…
Where is the syllable priming effect in visual word recognition?
2003
Recent studies using the masked priming paradigm have reported facilitating effects of syllable primes in French and English word naming (Ferrand, Segui, & Grainger, 1996; Ferrand, Segui, & Humphreys, 1997). However, other studies have not been able to replicate these effects in Dutch and English (Schiller, 1998, 1999, 2000). In Experiment 1, using the same stimuli and procedure as Ferrand et al. (1996), we did not replicate the syllable priming effect in French. In Experiments 2a and 2b, when prime duration was increased (from 30 to 45 and 60 ms), we did not obtain a syllable priming effect. In Experiment 3, with 60 participants and exactly the same procedure as Ferrand et al. (1996), we a…