When Prof. Hojjat Adeli, a Clarivate Analytics Highly Cited
Researcher in three categories: Comp... more When Prof. Hojjat Adeli, a Clarivate Analytics Highly Cited
Researcher in three categories: Computer Science, Engineering, and Cross-Field received his Honoris Causa title by Universidad Politécnica de Madrid, surprised me with this generous laudatio.
Thanks Hojjat!.
Page 1. Diego Andina DucTruongPham Editors for Engineering an Page 2. Computational Intelligence ... more Page 1. Diego Andina DucTruongPham Editors for Engineering an Page 2. Computational Intelligence Page 3. Computational Intelligence for Engineering and Manufacturing Edited by Diego Andina Technical University of Madrid ...
The control of the security in a limited area, like a house, is a complex task. This paper propos... more The control of the security in a limited area, like a house, is a complex task. This paper proposc a stand-alone intelligent system based on image recogiiit~on. The system detects moving peisoiis and successive update steps are applied in order to track them pviding important information about the position and their activity in term oi'traiectories perlbrined. Finally, a verification subsystem. based on the Intrusioti Detection System (IDS) used in coinputer networks technology attempts to identify unauthorized proximity based on ntrrinality patterns. 1. IN'I'RC)DUCTION Automatic human detection and body part lucalization arc important and challenging prohleins in compufer vision (1).(2). The solution to those prohleins cilii be einploycd in a wide nnge of applications such as safe robot navigation, visual surveillance, huinan-computer intcrl'ace, and figure animation. Our application doinnin is Domotics, i.e. the integral automation of huildings and housing. We can dcline it as: "A scr of eleincnts that, when installed, interconnected and cotitrolled autoinatically in a building. save the users wonying about routine weiyday actions, providing improvement in their coinfoii. in encrgy consumption. in security and iii conmimicarion as well". The context for human detectivn is the general ob,ject detection problem. Our approach is IO lirst seginetit Ibregruund ob.jects fium the hackground and then classify cach segmented ohject as human or non-human. Classifying only seginentcd ohjeots rather than searching them in the whole image significantly reduces computational complexity. Due to thr application domain of our system, we do not care about the classification of moving objccts as persons. So, we deal every inoving ab,icct as a threat for the security of the house. The tinal Intrusion I3etection subsystem based vti the shape ond trnjectories followed by tlic object should discriminate if this object is compromising the user defined security areas. The orgatiization ol the paper is 21s fAlows. First we review the work done for the European I'ro,ject Eureka EU- 136 I, which makes use of segmentation of forcginund ohjccls to pre-proccss vidcoconference scenes. The dctected ohjects are tracked using a mhiist regression scheme that will dcscribe their trqjectories using affitirr motion inodel parameters. Both the shape and tra.jectorics are used as the input for an Intrusion Detection System ((lF.), which is hascd on previous research done for detecting attacks 011 computer networks (3). The IDS attempts to idcntify unauthorized proximity to the high sccurity areas louking for statistical and rule-bnsed onnmaltes. Thcse high security areas are detined previously by the user of the system with an interact i ve i 11 terfacc.
One of the mayor limitations associated to Neural Networks (NNs) learning algorithms is the numbe... more One of the mayor limitations associated to Neural Networks (NNs) learning algorithms is the number of input-output pattern pairs needed to obtain the desired classilication pcrlbmancc. In many practical cases, the number 01' pairs used to design the NN is much lower than necessary. Either bccause of the excessivc price of data acquisition or, simply, for availability reasons. An Importance
In the first half of this book, Chapters 1 to 5, we have presented the foundations of information... more In the first half of this book, Chapters 1 to 5, we have presented the foundations of information risk management (Chapter 1), the profiles required by an IT security team (Chapter 2), the basic aspects that guide the team-individual contract (Chapter 3), a list of security principles to follow and activities to perform by the team (Chapter 4) and some
International Journal of Pattern Recognition and Artificial Intelligence, Oct 9, 2017
A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to iden... more A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to identify the typical pixels, as well as the less representative pixels or atypical of each segmented region. This method is based on the Possibilistic Fuzzy c-Means (PFCM) clustering algorithm, as it integrates absolute and relative memberships. Now, the segmentation problem is related to isolate each one of the objects present in an image. However, and considering only one segmented object or region represented by gray levels as its only feature, the totality of pixels is divided in two basic groups, the group of pixels representing the object, and the others that do not represent it. In the former group, there is a sub-group of pixels near the most representative element of the object, the prototype, and identified here as the typical pixels, and a sub-group corresponding to the less representative pixels of the object, which are the atypical pixels, and generally located at the borders of the pixels representing the object. Besides, the sub-group of atypical pixels presents greater tones (brighter or towards the white color) or smaller tones (darker or towards black color). So, the sub-segmentation method offers the capability to identify the sub-region of atypical pixels, although without performing a differentiation between the brighter and the darker ones. Hence, the proposal of this work contributes to the problem of image segmentation with the improvement on the detection of the atypical sub-regions, and clearly recognizing between both kind of atypical pixels, because in many cases only the brighter or the darker atypical pixels are the ones that represent the object of interest in an image, depending on the problem to be solved. In this study, two real cases are used to show the contribution of this proposal; the first case serves to demonstrate the pores detection in soil images represented by the darker atypical pixels, and the second one to demonstrate the detection of microcalcifications in mammograms, represented in this case by the brighter atypical pixels.
A Comparison of Criterion Functions for a Neural Network Applied to Binary Detection Diego ANDINA... more A Comparison of Criterion Functions for a Neural Network Applied to Binary Detection Diego ANDINA, Jose L. SANZ-GONZALEZ and Jose.A. JIMENEZ-PAJARES Departamento de Senates, Sistemas y Radiocomunicaciones, ETSI de Telecomunicacion, Universidad ...
When Prof. Hojjat Adeli, a Clarivate Analytics Highly Cited
Researcher in three categories: Comp... more When Prof. Hojjat Adeli, a Clarivate Analytics Highly Cited
Researcher in three categories: Computer Science, Engineering, and Cross-Field received his Honoris Causa title by Universidad Politécnica de Madrid, surprised me with this generous laudatio.
Thanks Hojjat!.
Page 1. Diego Andina DucTruongPham Editors for Engineering an Page 2. Computational Intelligence ... more Page 1. Diego Andina DucTruongPham Editors for Engineering an Page 2. Computational Intelligence Page 3. Computational Intelligence for Engineering and Manufacturing Edited by Diego Andina Technical University of Madrid ...
The control of the security in a limited area, like a house, is a complex task. This paper propos... more The control of the security in a limited area, like a house, is a complex task. This paper proposc a stand-alone intelligent system based on image recogiiit~on. The system detects moving peisoiis and successive update steps are applied in order to track them pviding important information about the position and their activity in term oi'traiectories perlbrined. Finally, a verification subsystem. based on the Intrusioti Detection System (IDS) used in coinputer networks technology attempts to identify unauthorized proximity based on ntrrinality patterns. 1. IN'I'RC)DUCTION Automatic human detection and body part lucalization arc important and challenging prohleins in compufer vision (1).(2). The solution to those prohleins cilii be einploycd in a wide nnge of applications such as safe robot navigation, visual surveillance, huinan-computer intcrl'ace, and figure animation. Our application doinnin is Domotics, i.e. the integral automation of huildings and housing. We can dcline it as: "A scr of eleincnts that, when installed, interconnected and cotitrolled autoinatically in a building. save the users wonying about routine weiyday actions, providing improvement in their coinfoii. in encrgy consumption. in security and iii conmimicarion as well". The context for human detectivn is the general ob,ject detection problem. Our approach is IO lirst seginetit Ibregruund ob.jects fium the hackground and then classify cach segmented ohject as human or non-human. Classifying only seginentcd ohjeots rather than searching them in the whole image significantly reduces computational complexity. Due to thr application domain of our system, we do not care about the classification of moving objccts as persons. So, we deal every inoving ab,icct as a threat for the security of the house. The tinal Intrusion I3etection subsystem based vti the shape ond trnjectories followed by tlic object should discriminate if this object is compromising the user defined security areas. The orgatiization ol the paper is 21s fAlows. First we review the work done for the European I'ro,ject Eureka EU- 136 I, which makes use of segmentation of forcginund ohjccls to pre-proccss vidcoconference scenes. The dctected ohjects are tracked using a mhiist regression scheme that will dcscribe their trqjectories using affitirr motion inodel parameters. Both the shape and tra.jectorics are used as the input for an Intrusion Detection System ((lF.), which is hascd on previous research done for detecting attacks 011 computer networks (3). The IDS attempts to idcntify unauthorized proximity to the high sccurity areas louking for statistical and rule-bnsed onnmaltes. Thcse high security areas are detined previously by the user of the system with an interact i ve i 11 terfacc.
One of the mayor limitations associated to Neural Networks (NNs) learning algorithms is the numbe... more One of the mayor limitations associated to Neural Networks (NNs) learning algorithms is the number of input-output pattern pairs needed to obtain the desired classilication pcrlbmancc. In many practical cases, the number 01' pairs used to design the NN is much lower than necessary. Either bccause of the excessivc price of data acquisition or, simply, for availability reasons. An Importance
In the first half of this book, Chapters 1 to 5, we have presented the foundations of information... more In the first half of this book, Chapters 1 to 5, we have presented the foundations of information risk management (Chapter 1), the profiles required by an IT security team (Chapter 2), the basic aspects that guide the team-individual contract (Chapter 3), a list of security principles to follow and activities to perform by the team (Chapter 4) and some
International Journal of Pattern Recognition and Artificial Intelligence, Oct 9, 2017
A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to iden... more A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to identify the typical pixels, as well as the less representative pixels or atypical of each segmented region. This method is based on the Possibilistic Fuzzy c-Means (PFCM) clustering algorithm, as it integrates absolute and relative memberships. Now, the segmentation problem is related to isolate each one of the objects present in an image. However, and considering only one segmented object or region represented by gray levels as its only feature, the totality of pixels is divided in two basic groups, the group of pixels representing the object, and the others that do not represent it. In the former group, there is a sub-group of pixels near the most representative element of the object, the prototype, and identified here as the typical pixels, and a sub-group corresponding to the less representative pixels of the object, which are the atypical pixels, and generally located at the borders of the pixels representing the object. Besides, the sub-group of atypical pixels presents greater tones (brighter or towards the white color) or smaller tones (darker or towards black color). So, the sub-segmentation method offers the capability to identify the sub-region of atypical pixels, although without performing a differentiation between the brighter and the darker ones. Hence, the proposal of this work contributes to the problem of image segmentation with the improvement on the detection of the atypical sub-regions, and clearly recognizing between both kind of atypical pixels, because in many cases only the brighter or the darker atypical pixels are the ones that represent the object of interest in an image, depending on the problem to be solved. In this study, two real cases are used to show the contribution of this proposal; the first case serves to demonstrate the pores detection in soil images represented by the darker atypical pixels, and the second one to demonstrate the detection of microcalcifications in mammograms, represented in this case by the brighter atypical pixels.
A Comparison of Criterion Functions for a Neural Network Applied to Binary Detection Diego ANDINA... more A Comparison of Criterion Functions for a Neural Network Applied to Binary Detection Diego ANDINA, Jose L. SANZ-GONZALEZ and Jose.A. JIMENEZ-PAJARES Departamento de Senates, Sistemas y Radiocomunicaciones, ETSI de Telecomunicacion, Universidad ...
Emerging and novel Bioinspired Artificial Neural Networks (BIANN) provide new interdisciplinary a... more Emerging and novel Bioinspired Artificial Neural Networks (BIANN) provide new interdisciplinary approaches for solution of complicated and intractable problems. How can engineering, mathematics, computation, Artificial Intelligence (AI) and Knowledge Engineering (KE) find inspiration in the behavior and internal functioning of physical, biological nervous systems to conceive, develop and build-up new concepts, materials, mechanisms and algorithms of potential value for solution of real world applications? And how can these techniques be used to conceptualize and model the nervous system? The aim of this special issue is research on the intersection of neurosciences and artificial neural networks and computations. Novel, emerging, and high impact BIANN theories and models with applications to illustrate their potential are welcome. Please inform the guest editors and the Editor-in-Chief about your intention to submit a manuscript for possible publication in the special issue as soon as possible. Please email the following to one of the Guest Editors with a copy to the Editor-in-Chief by March 15, 2016:
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Researcher in three categories: Computer Science, Engineering, and Cross-Field received his Honoris Causa title by Universidad Politécnica de Madrid, surprised me with this generous laudatio.
Thanks Hojjat!.
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Researcher in three categories: Computer Science, Engineering, and Cross-Field received his Honoris Causa title by Universidad Politécnica de Madrid, surprised me with this generous laudatio.
Thanks Hojjat!.