[visionlist] Computer Vision and Machine Learning (CVML) and Autonomous Systems Web Lecture Series

Fri Dec 4 04:27:48 -04 2020

Dear Computer Vision, Machine Learning and Autonomous Systems  engineers,
scientists and enthusiasts,

you are welcomed to register in the  'Computer Vision, Machine Learning and
Autonomous Systems Web Lecture Series'.

After the very successful completion of a) the Spring2020 edition of the
CVML Web Lecture Series and b) the 'Summer School on Autonomous Systems
2020' 17-21/8/2020, attracting more than 100 registrants, AIIA Lab
(AIIA.CVML research group) offers an asynchronous mode to study Computer
Vision, Machine Learning and Autonomous Systems topics. CVML Web Lecture
list is found below. Sample material of this course is available and lecture
topics are provided as well.

This asynchronous e-course provides an overview and in-depth presentation of
the various computer vision and deep learning problems encountered in
autonomous systems perception, e.g. in drone imaging or autonomous car
vision. It consists of 21 one-hour lectures and related material (ppt/pdf,
self-assessment exercises, videos, 5 programming exercises), covering the
following topics:

a. Computer vision. After reviewing image acquisition, camera geometry
(mapping the 3D world on a 2D image plane) and camera calibration, stereo
and multi-view imaging systems are presented for recovering 3D world
geometry from 2D images. This is complemented by Structure from Motion (SfM)
towards Simultaneous Localization and Mapping (SLAM) for vehicle and/or
target localization and visual object tracking and 3D localization. Motion
estimation algorithms are also overviewed. 
b. Neural Networks and Deep Learning. As there is much hype and often little
accuracy, when treating these topics, first the principles of Machine
Learning are presented, focusing on classification and egression. Then, an
introduction to neural networks, provides rigorous formulation of the
optimization problems for their training, starting with Perceptron. It
continues with Multilayer perceptron training through Backpropagation,
presenting many related problems, such as over-/under-fitting and
generalization. Deep neural networks, notably Convolutional NNs are the core
of this domain nowadays and they are overviewed in great detail. Their
application on deep learning for object detection is a very important issue
as well, complemented with a presentation of deep semantic image
segmentation.
c. Autonomous Systems. First of all, an introduction to Autonomous Systems
(AS) provides an overview of various issues related to AS perception and
control. Then topics related to autonomous drones are detailed, notably
drone mission planning and control and multiple drone imaging. Then
Autonomous cars and autonomous marine vehicles are overviewed.
d. CVML algorithms and programming. Various such tools, libraries and
frameworks are overviewed: Robotic Operating System (ROS), linear algebra
libraries (BLAS), DNN libraries (e.g., cuBLAS, cuDNN) and frameworks (e.g.,
Pytorch, Tensorflow, Keras etc). Distributed computing frameworks (Apache
Spark) and collaborative SW development tools are overviewed as well (e.g.,
GitHub). 
e. Signals and Systems. Much confusion exists nowadays in ML literature, as
even mature ML scientists have no background on Signals and Systems (SS) and
confuse even basic notions, e.g., convolutions and correlations. SS
principles are overviewed, while focusing on fast convolution algorithms,
particularly on 2D convolution algorithms that are an absolute must for CNN
libraries/frameworks and many computer vision tasks.

You can use the following link for course registration:

http://icarus.csd.auth.gr/cvml-web-lecture-series/

Lecture topics, sample lecture ppts and videos, self-assessment
questionnaires and programming exercises can be found therein.

For questions, please contact: Ioanna Koroni <koroniioanna at csd.auth.gr
<mailto:koroniioanna at csd.auth.gr> >

The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow,
Chair of the IEEE SPS Autonomous Systems Initiative, Director of the

Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle
University of Thessaloniki, Greece, Coordinator of the European Horizon2020

R&D project Multidrone. He is ranked 249-top Computer Science and
Electronics scientist internationally by Guide2research (2018). He is head

of the EC funded AI doctoral school of Horizon2020 EU funded R&D project
AI4Media (1 of the 4 in Europe). He has 31600+ citations to his work 

and h-index 85+.

AUTH is ranked 153/182 internationally in Computer Science/Engineering,
respectively, in USNews ranking.

Relevant links:

1) Prof. I. Pitas:

https://scholar.google.gr/citations?user=lWmGADwAAAAJ
<https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el> &hl=el

2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/

3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/

4) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/

5) AIIA Lab: https://aiia.csd.auth.gr/

LECTURES
Computer vision

1.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_1>
Introduction to computer vision
2.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_2> Image
acquisition, camera geometry
3.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_3> Stereo
and Multiview imaging
4.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_4> Structure
from motion
5.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_5>
Localization and mapping
6.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_6> Object
tracking and 3D localization
7.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cv_7> Motion
estimation 

Machine Learning

1.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ml_1>
Introduction to Machine Learning
2.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ml_2>
Introduction to neural networks, Perceptron
3.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ml_3>
Multilayer perceptron. Backpropagation
4.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ml_4> Deep
neural networks. Convolutional NNs
5.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ml_5> Deep
learning for object detection
6.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ml_6> Deep
Semantic Image Segmentation

Autonomous Systems

1.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#as_1>
Introduction to autonomous systems
2.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#as_2>
Introduction to multiple drone systems
3.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#as_3> Drone
mission planning and control
4.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#as_4>
Introduction to car vision
5.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#as_5>
Introduction to autonomous marine vehicles

CVML algorithms and programming

1.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#cvml_1> CVML
programming tools

Signals and Systems

1.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#ss_1> Fast 1D
convolution algorithms
2.	 <http://icarus.csd.auth.gr/cvml-web-lecture-series/#as_2> Fast 2D
convolution algorithms

CVML PROGRAMMING EXERCISES

Υou can improve your programming knowledge on Computer Vision, Machine
Learning and Image/Video Processing topics through programming exercises
using OpenCV, PyTorch and CUDA on the following topics:

1.	 <https://aiia.csd.auth.gr/introduction-to-opencv-programming/>
Introduction to OpenCV Programming
2.	 <https://aiia.csd.auth.gr/cnn-image-classification/> CNN image
classification
3.
<https://aiia.csd.auth.gr/pytorch-for-deep-object-detecti%ce%bfn-exercise/>
PyTorch for deep object detection
4.	 <https://aiia.csd.auth.gr/opencv-object-tracking-exercise/> OpenCV
programming for object tracking
5.
<https://aiia.csd.auth.gr/cuda-programming-of-2d-convolution-algorithms/>
CUDA programming of 2D convolution algorithms

SELF-ASSESSMENT

You can now assess your CVML knowledge and background by performing the
exercise described in: 
 <https://aiia.csd.auth.gr/cvml-knowledge-self-assessment/>
https://aiia.csd.auth.gr/cvml-knowledge-self-assessment/

Sincerely yours

Prof. I. Pitas

Director of the Artificial Intelligence and Information analysis Lab (AIIA
Lab)

Aristotle University of Thessaloniki, Greece

Post scriptum: To stay current on CVML matters, you may want to register to

the CVML email list, following instructions in

https://lists.auth.gr/sympa/info/cvml

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