A T M S Advanced Technologies For Medicine and Signals

A T M S مخبر البحث في التكنولوجيات المتقدمة في الإشارة و الطب



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KEYNOTE SPEAKERS


mounim_elyacoubi

Mounîm A. EL Yacoubi


CNRS, SAMOVAR,
Telecom SudParis -Paris Saclay University
FRANCE

Title:

Representation Learning: Deep and non-Deep Paradigms, and their Role in Building Effective Machine Learning Systems

Abstract:

Statistical pattern recognition has been dominated, over the last fifty years, by machine learning algorithms relying on handcrafted features that depend on the application at hand. Few of these algorithms, nonetheless, were based on features that are automatically learned from the data. The term Representation learning is coined to describe this latter category. Previously, representation learning was essentially shallow with techniques such as Principal component analysis, or Linear Discriminant Analysis. These techniques, however, were quickly outperformed with handcrafted features specifically designed for each applicative task.
Over the last decade, a breakthrough has been made with deep representation learning that automatically uncovers features from the raw data in a hierarchical way, with the ability of capturing the semantic content from the data.
In this presentation, I will discuss shallow and deep representation learning paradigms, and will shed light on the reasons behind the success of the deep representation category. I will also discuss some of the tasks we have addressed in my lab, with successful representation learning techniques in some non-obvious applications.

Biography:

Mounîm A. El-Yacoubi obtained a PhD in Signal Processing & Telecommunications from University of Rennes, France, in 1996. During his PhD thesis, he was with the R&D department of the Service de Recherche Technique de la Poste (SRTP) at Nantes, France, then directed by Michel Gilloux, where he developed Handwritten Address Recognition software that is still running in current French mail sorting machines, especially the first French handwritten street name recognition engine. He was a visiting scientist for 18 months at the Centre for Pattern Recognition and Machine Intelligence (CENPARMI) in Montreal, Canada, directed by Prof Ching Y. Suen, where he continued developing address recognition based on Hidden Markov Models. In 1998-2000, he become an associated professor at the Catholic University of Parana (PUC-PR) in Curitiba, Brazil, and was one of the cofounders of a research lab on document analysis in collaboration with CENPARMI and l’Ecole de Technologie Supérieure de Montréal. From 2001 to 2008, he was a Senior Scientist at Parascript, Boulder (CO, USA), a world leader company in automatic document processing, where he developed high-performance software for handwritten and machine print address, check and form recognition, still running today in Automatic reading systems in several countries across the world. Since June 2008, he is a Professor at Telecom SudParis, an engineering school, that is a member of both Institut Mines-Telecom and Paris Saclay University. His main interest lies in modeling, based on Machine Learning, human user data, especially behavioral signals like Handwriting and Gestures, with applications in e-health, human-computer interaction, and human mobility.




mauro dalla mura

Mauro DALLA MURA


Grenoble INP, FRANCE
FRANCE

Title:

Feature Analysis and Unsupervised Learning (Part I)

Abstract:

Biography:

Dr. Mauro Dalla Mura (S'08 – M'11) received the laurea (B.E.) and laurea specialistica (M.E.) degrees in Telecommunication Engineering from the University of Trento, Italy, in 2005 and 2007, respectively. He obtained in 2011 a joint Ph.D. degree in Information and Communication Technologies (Telecommunications Area) from the University of Trento, Italy and in Electrical and Computer Engineering from the University of Iceland, Iceland. In 2011 he was a Research fellow at Fondazione Bruno Kessler, Trento, Italy, conducting research on computer vision. He is currently an Assistant Professor at Grenoble Institute of Technology (Grenoble INP), France. He is conducting his research at the Grenoble Images Speech Signals and Automatics Laboratory (GIPSA-Lab). His main research activities are in the fields of remote sensing, image processing and pattern recognition. In particular, his interests include mathematical morphology, classification and multivariate data analysis. Dr. Dalla Mura was the recipient of the IEEE GRSS Second Prize in the Student Paper Competition of the 2011 IEEE IGARSS 2011 and co-recipient of the Best Paper Award of the International Journal of Image and Data Fusion for the year 2012-2013 and the Symposium Paper Award for IEEE IGARSS 2014. Dr. Dalla Mura is the President of the IEEE GRSS French Chapter since 2016 (he previously served as Secretary 2013-2016). In 2017 the IEEE GRSS French Chapter was the recipient of the IEEE GRSS Chapter Award and the “Chapter of the year 2017” from the IEEE French Section. He is on the Editorial Board of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS) since 2016.





bhiksha_raj

Bhiksha RAJ


Carnegie Mellon University, Pittsburgh,
PA, United States

Title:

End-to-end Speech Recognition with Deep Neural Networks

Abstract:

Biography:

Bhiksha Raj is a professor in the School of Computer Science, at Carnegie Mellon University. Dr. Raj obtained his PhD from CMU in 2000 and was at Mistubishi Electric Research Laboratories from 2001-2008. Dr. Raj's chief research interests lie in computer audition, machine learning, deep learning, and data privacy. Dr. Raj is a fellow of the IEEE.





ali_khenchaf

Ali KHENCHAF


Lab STICC UMR CNRS 6285 Laboratory,
ENSTA Bretagne, 29806, Brest,
cedex 09, FRANCE

Title:

Wave propagation, EM interaction and Remote sensing Application to the observation and extraction of parameters of the sea surface

Abstract:

In the context of the observation of the Earth's surface, remote sensing and radar imagery in the general sense make an important contribution in terms of the information collected on the areas and objects observed, and there are many different applications (territorial surveillance, cartography, oceanography, agriculture, glaciology, marine pollution, ...). This type of imaging system makes it possible, among other things, to measure the movement of the ocean surface, including the currents or wakes of ships. However, in order to contribute to the control of a situation above the surface it would be important to combine several aspects (from the sensor through the propagation medium to the processing of signals and / or images). For example, a radio link in the vicinity of the sea surface has its characteristics deeply affected by the presence of the ocean surface. Indeed, the signal from the direct path will be added a number of signals from multiple paths related to reflections from the objects and / or points of the surface. This results in interference between the direct path and the multiple paths resulting in fluctuations in the amplitude and phase of the resulting signal. These fluctuations are a function of the geometry of the link, its electromagnetic characteristics, as well as the state of the sea that depends on the weather conditions. Thus, the control of a situation above the surface is mainly through the characterization and understanding of the electromagnetic phenomena of the environment. And this is reflected directly first by the study of the propagation and interactions of electromagnetic waves with natural environments (atmosphere, rain cloud, sea, soil, forest ...) in the presence of targets or objects. Then by the control of the sensors, the understanding and realistic simulation of the monostatic or bistatic connections (of observation and / or satellites, of perception or communication) placed in this disturbed and evolutionary environment. Finally, the processing and extraction of information from a database of signals (n-D) from different sensors or after transformation constitute one of the last elements of the chain. The objective of this last element is to obtain and merge a greater amount of knowledge and information from the observed scene in order to improve the recognition and automatic identification of targets embedded in a disturbed environment. These different aspects and difficulties will be the subject of the presentation. The illustrations will be based on measurements (generated or real), the works published over several years and made in the context of different partnerships at the same time industrial, university or state.
Keywords: sensors, environment, propagation, wave interaction, radar targets, EM signature, clutter, radar imagery, detection, classification, indexing and image search, reconnaissance, remote sensing, ...

Biography:

Ali Khenchaf received the M.S. degree in statistical data processing from the University of Rennes I, Rennes, France, in 1989. In 1992, he received his Ph.D degree in Electronic Systems and Computer Network from the University of Nantes. From 1989 to 1993, he was a Researcher with the IRCCyN (UMR CNRS 6597) Laboratory, Nantes, and was an Assistant Professor from 1993 to 2001. Since September 2001, he has been with ENSTA Bretagne (Ex. ENSIETA), Brest, France, where he is currently a Professor and, from 2001 to 2011, Head of the E3I2 Laboratory (EA 3876). He joined, since January 2012, the laboratory Lab-STICC UMR CNRS 6285, where he is co-responsible of "Propagation and Interaction Multi-scales" team. The research conducted by Ali Khenchaf for over twenty five years in several laboratories are oriented towards both electromagnetic modeling and simulation, and also to the extraction and exploitation of information derived from phenomena induced by the interaction of electromagnetic waves with the environment and / or complex objects (especially sea clutter and detection problems). These activities are designed especially to integrate more "intelligence" in operational systems (airborne, satellite, drone, ...), which are dedicated to perception and observation of the natural environment. His research and teaching courses are in the fields of numerical mathematics, electromagnetic wave propagation, waves and microwave and signal processing. His research interests include radar wave scattering, microwave remote sensing, electromagnetic wave propagation, scattering in random media, monostatic and bistatic scattering of electromagnetic waves, target Radar Cross Section, Radar Imagery and target parameter estimation. He has edited or co-edited three books and author or co-authored over 300 scientific articles. He assumed responsibility of more than 40 scientific projects contracted in partnership with industry and other organizations. He also led or co-directed more than 40 students PhD thesis. Since January 2017, he has been a member of the Editorial Board of the European Journal of Remote Sensing. And professor Khenchaf is currently guest editor of the journal "Remote sensing". In addition, Ali Khenchaf is expert with several agencies and organizations in France and abroad.




Eloi-bosse

Éloi Bossé


Expertises Parafuse Inc. (Québec), and researcher
McMaster University (Hamilton),
CANADA

Title:

Fusion of Information and Analytics Technologies (FIAT) for Big Data and IoT

Abstract:

Information overload and complexity are core problems to both military and civilian complex systems, networks and organizations of today. The advances in networking capabilities have created the conditions of complexity by enabling richer, real-time interactions between and among individuals, objects, systems and organizations. On the other hand, what is considered as problems for system designers is technological opportunities for deciders, for instance, the Internet of Things and the Big Data. Fusion of Information and Analytics Technologies (FIAT) are key enablers to bring these benefits to deciders. The design of current and future decision support systems (real-time, online, and near real-time) make use of FIAT to support prognosis, diagnosis, and prescriptive tasks for systems. Hundreds of methods and technologies exist, and several books have been dedicated to either analytics or information fusion so far. However, very few have discussed the methodological aspects and the need of an integrating framework or a computational model for an integration of these techniques coming from multiple disciplines. This plenary speech presents anoverview of potential integrating frameworks as well as a description of elements that will support the development of a computational model to evolve FIAT-based systems capable of meeting the challenges of complex systems.

Biography:

Éloi Bossé, Ph.D.,received the B.A.Sc. (79), M.Sc. (81) and Ph.D (90) degrees from Université Laval, QC, in Electrical Engineering. In 1981 he joined the Communications Research Centre, Ottawa, Canada, where he worked on signal processing and high resolution spectral analysis. In 1988 he was transferred to the Defence Research Establishment Ottawa to work on radar target tracking in multipath. In (1992) he moved to Defence Research and Development Canada Valcartier (DRDC Valcartier) to lead a group of 4-5 defence scientists on information fusion and resource management. He has published over 200 papers in journals, book chapters, conference proceedings and technical reports. Dr.Bossé has held adjunct professor positions at several universities from 1993-2013 (Université Laval, University of Calgary and McMaster University). He headed the C2 Decision Support Systems Section at DRDC Valcartier from 1998 till 2011. Dr.Bossé was the Executive Chair of the 10th International Conference on Information Fusion (FUSION`07), held in July 2007 in Québec City. He represented Canada (as DRDC member) in numerous international research fora under the various cooperation research programs (NATO, TTCP, bi and tri-laterals) in his area of expertise. He is co-author and co-editor of 4-5 books on information fusion. He retired from DRDC in Sept. 2011. Since then, he conducted some research activities under NATO Peace and Security Programme, as researcher in Mathematics and Industrial Engineering Department at Polytechnic of Montreal, as researcher at McMaster University (Hamilton, Ontario, Canada), as associate researcher at IMT-Atlantique and, since 2015, as president of Expertise Parafuse Inc., a consultant firm on Analytics and Information Fusion technologies.