SINC(i)

Transcription

SINC(i)

Machine learning and signal processing
Bioinformatics, biomedical technology, energy, speech, video,...
Big Data Argentina 2013
Diego Milone
sinc(i )
C O N I CE T
Research Center for Signals,
Systems and Computational Intelligence
Departament of Informatics
Faculty of Engineering and Water Sciences (FICH)
Universidad Nacional del Litoral (UNL)
National Scientific and Technical Research Council (CONICET)
About sinc(i)
Big data?
People at sinc(i)
Research Staff
UNL-UNER
CONICET-UNL
CONICET-UNL
UNER∗ CONICET
CONICET-UTN-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL-UNER
CONICET-UNL
UNER∗ UNL-CONICET
sinc(i )
Cesar E. Martínez
Diego H. Milone
Diego R. Tomassi
Gastón Schlotthauer
Georgina S. Stegmayer
Leandro E. Di Persia
Leandro D. Vignolo
Leonardo L. Giovanini
H. Leonardo Rufiner
E. Marcelo Albornoz
María Eugenia Torres
12: 53
Diego Milone (sinc(i)-UNL-CONICET)
BigDatAr: Machine Learning & Signal Proc.
August 27, 2013
2 / 32
About sinc(i)
Big data?
People at sinc(i)
Research Staff
Cesar E. Martínez
Diego H. Milone
Diego R. Tomassi
Leandro D. Vignolo
H. Leonardo Rufiner
E. Marcelo Albornoz
UNL-UNER
CONICET-UNL
CONICET-UNL
UNER∗ CONICET
CONICET-UTN-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL-UNER
CONICET-UNL
UNER∗ UNL-CONICET
Analía Cherniz
Carlos Pais+
David Campo
Fernando Sato+
Guido Sanchez
Guillermo Leale
Iván Gareis
Iván Peralta+
José Chelotti
Leandro Bugnon
Leonardo López
Matías Gerard
Mariano Rubiolo
Mariela Uhrig
Marina Murillo
Milton Pividori
Román Rolón
Rubén Acevedo
Sebastián Vanrell
Sergio Burgos+
Tomás Molas Gimenez
sinc(i )
Graduate Students
12: 53
August 27, 2013
2 / 32
About sinc(i)
Big data?
People at sinc(i)
Research Staff
Cesar E. Martínez
Diego H. Milone
Diego R. Tomassi
Leandro D. Vignolo
H. Leonardo Rufiner
E. Marcelo Albornoz
UNL-UNER
CONICET-UNL
CONICET-UNL
UNER∗ CONICET
CONICET-UTN-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL-UNER
CONICET-UNL
UNER∗ UNL-CONICET
Alejandro Fortvilla
Alejandro Sartori
Brisa Basconsel
Carim Fadil
Cecilia Balestieri
César Arrasin
Cristian Yones
Fernando Guerin
Franco Victorio
Eloisa Colignan
Hilarie Grieve
Leandro Burruchaga
Marcelo Caamaño
María Chelotti
Martín Musachio
Neri Cibau
Nicolás Mastaglia
Pablo Sosa
Ramiro Alvarez
Romina Galarza
Walter Schulte
sinc(i )
Undergraduate Students
12: 53
August 27, 2013
2 / 32
About sinc(i)
Big data?
People at sinc(i)
Research Staff
Cesar E. Martínez
Diego H. Milone
Diego R. Tomassi
Leandro D. Vignolo
H. Leonardo Rufiner
E. Marcelo Albornoz
UNL-UNER
CONICET-UNL
CONICET-UNL
UNER∗ CONICET
CONICET-UTN-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL
CONICET-UNL-UNER
CONICET-UNL
UNER∗ UNL-CONICET
Alejandro Azario
Alejandro Ronsoni
Belén Crolla
Carlos Sánchez Reinoso+
Carolina Gómez
Cristian Pfarher
Damián Richter
Diego Evin+
David Haimovich
Esteban Osella
Germán Scarel
German Burgener
Guillermo Korell
Juaquín Barreiro
Juan Barletta
Juan Pablo Vogt
Leandro Perren
Matías Meurzet
Mauro Torrez
Mónica Laresse
Soledad Padron
sinc(i )
Former Students
12: 53
August 27, 2013
2 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V∗
12: 53
∗
Modified from SIAM News, Volume 46, Number 6, July/August 2013.
August 27, 2013
5 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V∗
12: 53
∗
August 27, 2013
5 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V∗
12: 53
∗
August 27, 2013
5 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V∗
12: 53
∗
August 27, 2013
5 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V: Bioinformatics
12: 53
August 27, 2013
6 / 32
About sinc(i)
Big data?
sinc(i )
12: 53
August 27, 2013
12 / 32
About sinc(i)
Big data?
RILs
Aminoacids
Sugars
Organic acids
Fatty acids
Secondary mets.
Yield traits
sinc(i )

Fruit firmne




 Shelf life
Glycerate
Neuron 7


Malate



Fru (inv)
SS
Neuron 12
Pro
12: 53
August 27, 2013
13 / 32
About sinc(i)
Big data?
sinc(i )
August 27, 2013
14 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V: *omesom screenshot
August 27, 2013
15 / 32
About sinc(i)
Big data?
Proyects:
Self-Organization in *omic data
Data Integration and Ensemble Clustering
Biological Clustering from Gene Ontology
Evolutionary Metabolic Pathway Discovery
Inference of Gene Regulatory Networks
sinc(i )
miRNA Prediction
12: 53
August 27, 2013
16 / 32
About sinc(i)
Big data?
Proyects:
Self-Organization in *omic data
Data Integration and Ensemble Clustering
Biological Clustering from Gene Ontology
Evolutionary Metabolic Pathway Discovery
Inference of Gene Regulatory Networks
sinc(i )
miRNA Prediction
12: 53
August 27, 2013
16 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V: Audio, image, video
12: 53
August 27, 2013
17 / 32
About sinc(i)
Big data?
sinc(i )
12: 53
August 27, 2013
17 / 32
About sinc(i)
Big data?
Speech recognition
“en que ”
ASR System
t
Signal processing and analysis
Pattern recognition
Speech signal
Text
The problem complexities:
Speech continuity, context dependence
Inter/intra speaker variability
The structures of speech
Noise and other distortions
Vocabulary size: small medium large very large unrestricted
Speakers: mono- multi- independent
Speaking styles: isolated connected read fluent spontaneous
Distortions: robust/non-robust speech recognition
sinc(i )
Types of speech recognizers:
12: 53
August 27, 2013
18 / 32
About sinc(i)
Big data?
The speech recognition model
sinc(i )
ASR System
August 27, 2013
19 / 32
About sinc(i)
Big data?
s(t)
s[m,k]
e
B
silencio
l
está
s
en
o
el
t
sótano
a
del
n
comedor
o
silencio
E
Feature extraction
Classifier
sinc(i )
Language model
12: 53
August 27, 2013
20 / 32
About sinc(i)
Big data?
s(t)
s[m,k]
e
B
silencio
l
está
s
en
o
el
t
sótano
a
del
n
comedor
o
silencio
E
Feature extraction
Independent Component Analisys in Blind Source Separation
Multiresolution Entropies
Linear-Predictive Sparse Coding
Evolutionary Optimization of Wavelet Packets and Filterbanks
Classifier
sinc(i )
Language model
12: 53
August 27, 2013
20 / 32
About sinc(i)
Big data?
s(t)
s[m,k]
e
B
silencio
l
está
s
en
o
el
t
sótano
a
del
n
comedor
o
silencio
E
Sparse Representations and Classifier Ensembles
Cortical Neural Networks
Hidden Markov Models with Hidden Markov Trees (HMM-HMT)
Discriminative Training for HMM-HMT
Speech Segmentation based on Multiresolution Entropies
Language model
sinc(i )
Feature extraction
Classifier
12: 53
August 27, 2013
20 / 32
About sinc(i)
Big data?
s(t)
s[m,k]
e
B
silencio
l
está
s
en
o
el
t
sótano
a
del
n
comedor
o
silencio
E
Feature extraction
Classifier
Language model
sinc(i )
Prosody in Language Models
Time Variant Language Models
12: 53
August 27, 2013
20 / 32
About sinc(i)
Big data?
Man-Machine interfaces:
Emotions Recognition from Speech
Speaker Recognition
Face Identification
Hand Signs Recognition
Medical applications:
Classification of Pathological Voices
Automatic Recognition of Obstructive Sleep Apnoea/Hypopnoea Syndrome
Automatic Detection of Cardiac Pathologies
sinc(i )
Chromosome Recognition
12: 53
August 27, 2013
21 / 32
About sinc(i)
Big data?
sinc(i )
Masticatory events: Big Data?
12: 53
August 27, 2013
23 / 32
About sinc(i)
Big data?
Hidden Markov Models
bite
S
sil
chew
sil
sinc(i )
chew-bite
E
August 27, 2013
24 / 32
About sinc(i)
Big data?
sinc(i )
Big Data 4V: Energy, smart grid, sensor data
12: 53
August 27, 2013
25 / 32
About sinc(i)
Big data?
sinc(i )
12: 53
August 27, 2013
25 / 32
About sinc(i)
Big data?
sinc(i )
Simulation of photovoltaic centrals with dynamic shading
12: 53
August 27, 2013
27 / 32
About sinc(i)
Big data?
sinc(i )
Evolutionary design of photovoltaic centrals
12: 53
August 27, 2013
28 / 32
About sinc(i)
Big data?
Complex Systems:
Biological systems:
Metabolism
Ecology
Epidemiology
...
Vehicle autonomy:
Vehicle control
Assistive technology
Engine operation
...
Networked systems:
sinc(i )
Power generation and distribution systems
Communication systems
...
August 27, 2013
29 / 32
About sinc(i)
Big data?
sinc(i )
Signal Processing for Magnetic Resonance Solutions
12: 53
August 27, 2013
30 / 32
About sinc(i)
Big data?
Signal Processing for Magnetic Resonance Solutions
NMF, α optimo: 0.70215
6
x 10
NMF, α optimo: 0.62319
6
x 10
4
6
3.5
6
10
6
10
5
3
2.5
4
5
5
10
T2
T2
10
2
3
1.5
4
10
2
1
4
10
1
0.5
3
10
0
0.02 0.01
0
0
1
2
3
4
5
6
6
x 10
0.02
0.015
0.01
0.005
3
4
10
5
10
T1
6
10
0
0
0
0.025
0.02
0.015
0.01
0.005
3
10
1
2
3
4
5
6
7
6
x 10
4
10
5
10
T1
6
10
sinc(i )
10
0.02 0.01
12: 53
August 27, 2013
31 / 32
Thank you!
Machine learning and signal processing
Bioinformatics, biomedical technology, energy, speech, video,...
Big Data Argentina 2013
Diego Milone
sinc(i )
C O N I CE T
Research Center for Signals,
Systems and Computational Intelligence
www.fich.unl.edu.ar/sinc
Departament of Informatics
Faculty of Engineering and Water Sciences
Universidad Nacional del Litoral - CONICET
Ciudad Universitaria UNL - 3000 - Santa Fe - Argentina

SINC(i)

Transcription

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