Event Price: $885,000 COP
Event Price: 250 USD
Online payment: At the time of your registration you will be able to pay online with credit card and PSE.
Payment in banks:
Present the invoice printed in laser, and approach the following banking entities:
- Banco de Bogotá and its banking correspondents: Almacenes Éxito, Carulla, Surtimax, Súper inter.
Go to the University Cashier and pay with a debit or credit card.
Start date: 20-09-2021
End date: 22-11-2021
Duration: 40.00 hours.
Event city: Online
Hours: Monday and Wednesday, from September 20 to November 22, 2021, from 05:30 p.m. to 08:00 p.m.
Place: CES University
Event Code: 70110985
To register, you must fill out the form to generate the invoice and make the payment online, banks or in person at the University.
Know the importance of the topics to be addressed during the development of the Course
We share the characteristics or requirements that you must meet to be part of this Course
The modality of the event is Virtual Classroom
How far can the machines see? Computer Vision (CV) is one of the most innovative fields of artificial intelligence, which seeks to develop techniques for computers to "see" and understand the content of digital images, such as photographs and videos. The problems that the CV aims to solve are constituted by the classification, detection and recognition of both people and objects, in images acquired from all kinds of cameras and processed by means of computers. These problems that are trivial for humans are somewhat complex for machines, which is why it is necessary to develop effective algorithms to solve them.
Undergraduate and graduate students in Engineering, Professionals in the field of Image Analysis, Software Developers, Technology Managers and other stakeholders with basic knowledge in algorithm design, programming and mathematics.
Required prior knowledge: knowledge in basic mathematics (calculus, linear algebra), basic statistics, programming fundamentals and algorithms.
Required tools: computer with processor greater than 1.2GHz, RAM memory equal to or greater than 8GB, possibility of installation of free software, stable internet connection, microphone and camera (required for non-face-to-face classes).
Face-to-face assisted by technology or face-to-face with online transmission (as established by the University).
Find out how you can finance your registration in this event.
Find the contents to be dealt with in the Continuing Education Course
Learn about the skills that you will acquire by taking the Course at our University.
Finance the payment of your registration with SUFI, contact the advisor:
Anderson Esneyder Acevedo Benitez
Phone: (57) 604 604 91 25
Mobile: 301 254 98 44
Payment with Severance:
Check with your fund and severance management company about the requirements to make the payment *.
* Applies for diplomas and certifications.
- Introduction to computer vision and pixel manipulation.
- Operation on the image.
- Image filtering.
- Video acquisition and segmentation.
- Color spaces and color segmentation.
- Detection of edges and morphological operators.
- What are the characteristics and their different types.
- Descriptors and feature extraction.
- Creation of databases.
- Practice 1: Pixel manipulation and image transformation.
- Practice 2: Proprocessing and filtering images.
- Practice 3: Image segmentation, edge detection and application of morphological operators.
- Practice 4: Applications in automatic visual inspection.
At the end of the course, the participant will be able to analyze 2D and 3D images, obtained from free databases, using segmentation techniques, use of descriptors, detectors of objects and people, as well as image recording techniques and their application in medicine.
Master in Automation and Control from the Metropolitan Technological Institute, with emphasis on Machine Learning applied to images. He has extensive experience as a teacher in undergraduate courses and in Deep Learning Applications on images, as well as different publications in computer vision applications in indexed journals.
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