Date&Time: February 9, 2023 at 12:30
p.m. CET
[06:30 a.m. New-York] - [12:30 p.m. Paris] [13:30 p.m. Tampere]-
[6:30 p.m. Beijing]
Title: The Super Neuron Model
– A new generation of ANN-based Machine Learning and Applications
Speaker: Moncef Gabbouj, Tampere, University, Tampere, Finland.
To join the webinar, please register to receive more details on
how to connect. The registration form can be found at:
https://forms.gle/9JCc6NBgM1x2kZK6A
or via the website of the journal at:
https://jivp-eurasipjournals.springeropen.com/
Contact: Esinu Abadjivor
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Abstract: Operational Neural Networks (ONNs) are new generation
network models targeting to address two major drawbacks of
conventional Convolutional Neural Networks (CNNs): the homogenous
network configuration and the “linear” neuron model that can only
perform linear transformations over previous layer outputs. ONNs
can perform any linear or non-linear transformation with a proper
combination of “nodal” and “pool” operators. This is a great leap
towards expanding the neuron’s learning capacity in CNNs, which
thus far required the use of a single nodal operator for all
synaptic connections for each neuron. This restriction has
recently been lifted by introducing a superior neuron called the
“generative neuron” where each nodal operator can be customized
during the training in order to maximize learning. As a result,
the network is able to self-organize the nodal operators of its
neurons’ connections. Self-Organized ONNs (Self-ONNs) equipped
with superior generative neurons can achieve diversity even with a
compact configuration. We shall explore several signal processing
applications of neural network models equipped with the superior
neuron.
Speaker Bio: MONCEF GABBOUJ received his BS degree in 1985 from
Oklahoma State University, and his MS and PhD degrees from Purdue
University, in 1986 and 1989, respectively, all in electrical
engineering. Dr. Gabbouj is a Professor of Information Technology
at the Department of Computing Sciences, Tampere University,
Tampere, Finland. He was Academy of Finland Professor during
2011-2015. His research interests include Big Data analytics,
multimedia content-based analysis, indexing and retrieval,
artificial intelligence, machine learning, pattern recognition,
nonlinear signal and image processing and analysis, voice
conversion, and video processing and coding. Dr. Gabbouj is a
Fellow of the IEEE and member of the Academia Europaea and the
Finnish Academy of Science and Letters. He is the past Chairman of
the IEEE CAS TC on DSP and committee member of the IEEE Fourier
Award for Signal Processing. He served as associate editor and
guest editor of many IEEE, and international journals and
Distinguished Lecturer for the IEEE CASS. Dr. Gabbouj served as
General Co-Chair of IEEE ISCAS 2019, ICIP 2020, ICIP 2024 and ICME
2021. Gabbouj is Finland Site Director of the USA NSF IUCRC funded
Center for Visual and Decision Informatics (CVDI) and led the
Artificial Intelligence Research Task Force of Finland’s Ministry
of Economic Affairs and Employment funded Research Alliance on
Autonomous Systems (RAAS).
Webinar videos are available online at
https://vimeo.com/showcase/8005816.