Acerca de este Curso
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Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Aprox. 22 horas para completar

Inglés (English)

Subtítulos: Inglés (English)
User
Los estudiantes que toman este Course son
  • Machine Learning Engineers
  • Data Scientists
  • Technical Solutions Engineers
  • Software Engineers
  • Researchers

Qué aprenderás

  • Check

    Design and build image processing applications

  • Check

    Examine the different types of image transformations

  • Check

    Analyze images in frequency domain

  • Check

    Understand image features and segmentation

Habilidades que obtendrás

Image ProcessingImage SegmentationComputer ProgrammingMatlab
User
Los estudiantes que toman este Course son
  • Machine Learning Engineers
  • Data Scientists
  • Technical Solutions Engineers
  • Software Engineers
  • Researchers

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Aprox. 22 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
7 horas para completar

Image Processing Fundamentals

4 videos (Total 20 minutos), 2 lecturas, 8 cuestionarios
4 videos
Image Processing Basics4m
Intensity Transformations4m
Color Image Processing3m
2 lecturas
Resources (Optional): Image Processing Fundamentals30m
REQUIRED- MATLAB Resources10m
2 ejercicios de práctica
Image Processing Basics6m
Intensity Transformations5m
Semana
2
4 horas para completar

Image Filters

5 videos (Total 26 minutos), 1 lectura, 7 cuestionarios
5 videos
Filtering in Frequency Domain4m
Multi-Resolution Processing & Compression6m
Morphological Image Processing3m
Advanced Image Processing3m
1 lectura
Resources (Optional): Image Filters30m
5 ejercicios de práctica
Spatial Image Filtering20m
Filtering in Frequency Domain6m
Multi-Resolution Processing & Compression5m
Morphological Image Processing15m
Advanced Image Processing2m
Semana
3
2 horas para completar

Image Features & Matching

5 videos (Total 21 minutos), 1 lectura, 5 cuestionarios
5 videos
Scale Invariant Image Features5m
Feature Matching1m
Creating a Panorama4m
Texture Matching2m
1 lectura
Resources (Optional): Image Features and Matching30m
4 ejercicios de práctica
Image Features
Scale Invariant Image Features6m
Feature Matching2m
Texture Matching2m
Semana
4
3 horas para completar

Image Segmentation

6 videos (Total 15 minutos), 2 lecturas, 4 cuestionarios
6 videos
State-of-the-Art Image Segmentation2m
Early Segmentation Techniques3m
Segmentation & Clustering3m
Probabilistic Segmentation58s
Graph Cut Segmentation57s
2 lecturas
Resources (Optional): Image Segmentation30m
Image Processing, Features & Segmentation - Key Takeaways15m
2 ejercicios de práctica
Segmentation & Clustering6m
Probabilistic Segmentation2m

Instructores

Avatar

Radhakrishna Dasari

Instructor
Department of Computer Science
Avatar

Junsong Yuan

Associate Professor and Director of Visual Computing Lab
Computer Science and Engineering

Acerca de University at Buffalo

The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs....

Acerca de Universidad Estatal de Nueva York

The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe....

Acerca de Programa especializado Visión artificial

This specialization provides a foundation in the rapidly expanding research field of computer vision, laying the groundwork necessary for designing sophisticated vision applications. Learners explore the integral elements that enable vision applications, ranging from editing images to reading traffic signs in self-driving cars to factory robots navigating around human co-workers. Content includes image processing and state-of-the-art vision techniques, augmented by insights from top leaders in the computer vision field. Learners gain hands-on experience writing computer vision programs through online labs using MATLAB and supporting toolboxes. The specialization is taught in MATLAB* using computer vision and supporting toolboxes. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). To learn more, check out a video overview at https://youtu.be/OfxVUSCPXd0. * A free license to install MATLAB for the duration of the course is available from MathWorks....
Visión artificial

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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