Classification using Extended Morphological Attribute Profiles based on different feature extraction techniques

Peeters, Stijn; Marpu, Prashanth Reddy; Benediktsson, Jón Atli; Mura, Mauro Dalla

doi:10.1109/igarss.2011.6050221

Cited by 9 publications

(2 citation statements)

References 7 publications

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“…Voice recognition (Al-Sarayreh, Khalid T. et al, 2009) consists of two main tasks, that is, Feature Extraction system and model Recognition system. Feature extraction attempts to determine character of the sound signal, while model recognition refers to the analogous of features in such a way as to determine, within probabilistic limits, whether two sets of features are from the same or dissimilar domain (Peeters, S., Marpu, P. R., Benediktsson, J. A., & Dalla Mura, M., 2011).…”

Section: Voice Recognitionmentioning

confidence: 99%

A Novel Approach to Build a Generic Model of Photovoltaic Solar System Using Sound Biometric Techniques

Al-Sarayreh

Meridji

Fayyoumi

et al. 2014

International Journal of Information Technology and Web Engineering

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This chapter presents the proposed model of combination between Photovoltaic solar system resources and sound biometric techniques, to generate power energy from the sunlight using the PVS controlled by a sound biometric technique. This work contributes to research knowledge by proposing and validating a sound biometric technique for allowing to reduce the consumption of the generated power energy by turn the lights on for the public roads only when there are vehicles on the way and only for some period of time to make the driving out of harm's way and trouble-free. The proposed and combination models between the PVS and biometric sound chip is used for generating electric power by using solar cells to convert energy from the sun light into a flow of direct current electricity, which can be used to power equipment or to recharge a battery. In addition the Sound biometric techniques can enable PVS to listen and understand their surrounding auditory environment since turning the lights on all the time will get through a lot of energy which it might be used in other significant concerns.

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Section: Voice Recognitionmentioning

confidence: 99%

A Novel Approach to Build a Generic Model of Photovoltaic Solar System Using Sound Biometric Techniques

Al-Sarayreh

Meridji

Fayyoumi

et al. 2014

International Journal of Information Technology and Web Engineering

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“…In the literature [55], the Nonparametric Weighted Feature Extraction (NWFE) supervised method has been widely used to reduce the number of morphological features extracted by the morphological analysis (ESDAP). The NWFE technique is an efficient algorithm for high dimensional multi-class pattern recognition problems.…”

Section: Is As Followsmentioning

confidence: 99%

On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods

Cavallaro

Riedel

Richerzhagen

et al. 2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Abstract-Owing to the recent development of sensor resolutions on-board different Earth observation platforms, remote sensing is an important source of information for mapping and monitoring natural and man-made land covers. Of particular importance is the increasing amounts of available hyperspectral data originating from airborne and satellite sensors such as AVIRIS, HyMap, and Hyperion with very high spectral resolution (i.e., high number of spectral channels) containing rich information for a wide range of applications. A relevant example is the separation of different types of land cover classes using this data in order to understand for example impacts of natural disasters or changing of city buildings over time. More recently, such increases in the data volume, velocity, and variety of data contributed to the term "big data" that stands for challenges shared with many other scientific disciplines. On the one hand the amount of available data is increasing in a way that raises the demand for automatic data analysis elements since many of the available data collections are massively underutilized lacking experts for manual investigation. On the other hand, proven statistical methods (e.g.,, dimensionality reduction) driven by manual approaches have a significant impact in reducing the amount of "big data" towards smaller "smart data" contributing to the more recently used terms data value and veracity (i.e., less noise, lower dimensions that capture the most important information). This paper aims to take stock of which proven statistical data mining methods in remote sensing are used to contribute to "smart data" analysis processes in the light of possible automation as well as scalable and parallel processing techniques. We focus on parallel support vector machines (SVMs) as one of the best out-of-the-box classification methods.

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Remote Sensing Data Fusion: Markov Models and Mathematical Morphology for Multisensor, Multiresolution, and Multiscale Image Classification

Benediktsson

Cavallaro

Falco

et al. 2017

Mathematical Models for Remote Sensing Image Processing

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Classification using Extended Morphological Attribute Profiles based on different feature extraction techniques

Cited by 9 publications

References 7 publications

A Novel Approach to Build a Generic Model of Photovoltaic Solar System Using Sound Biometric Techniques

A Novel Approach to Build a Generic Model of Photovoltaic Solar System Using Sound Biometric Techniques

On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods

Remote Sensing Data Fusion: Markov Models and Mathematical Morphology for Multisensor, Multiresolution, and Multiscale Image Classification

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