Competencies and objectives

 

Course context for academic year 2023-24

La asignatura está ubicada en el primer semestre del Máster Universitario en Inteligencia Artificial e introduce al estudiante en el uso de las técnicas de visión artificial, con el objetivo de estudiar, a través de casos prácticos, la naturaleza o los sistemas óptimos de visión en las ingenierías, apoyándose en tecnologías de la información y las comunicaciones.

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees)

Transversal Competences

  • CT1 : Be able to lead projects related to artificial intelligence, as well as to manage work teams.
  • CT2 : Demonstrate computer and information skills in the field of artificial intelligence.
  • CT3 : Demonstrate oral and written communication skills.

 

General Competences

  • CG1 : Apply the knowledge acquired to real problems related to artificial intelligence.
  • CG10 : Be able to use engineering principles and modern computer technologies to research, design and implement new applications of artificial intelligence,
  • CG2 : Be able to develop and learn in a self-directed or autonomous way topics related to artificial intelligence.
  • CG3 : Know how to operate in multidisciplinary and/or international contexts, providing solutions from the point of view of artificial intelligence.
  • CG6 : Being able to adapt to environments related to artificial intelligence, fostering teamwork, creativity,
  • CG7 : To be able to adapt to the constant evolution of the discipline and to understand and apply new technical and scientific developments related to artificial intelligence.
  • CG8 : Knowing how to plan, design, develop, implement and maintain products, applications and services related to artificial intelligence, taking into account technical, economic and efficiency aspects.
  • CG9 : Know how to manage projects related to artificial intelligence, complying with current regulations and ensuring the quality of the service.

 

Specific Competences

  • CE06 : Know and apply image processing tools and techniques suitable for solving computer vision problems.
  • CE07 : Know and apply tools and techniques for the extraction of visual information suitable for the resolution of artificial vision problems.

 

Basic Competences

  • CB10 : Students possess the learning skills that will enable them to continue studying in a way that will be largely self-directed or autonomous. be largely self-directed or autonomous.
  • CB6 : Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
  • CB7 : Students should be able to apply their acquired knowledge and problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their field of study.
  • CB8 : Students are able to integrate knowledge and deal with the complexity of making judgements on the basis of incomplete or limited information, including reflections on the social and ethical responsibilities associated with information which, while incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgements.
  • CB9 : Students are able to communicate their conclusions and the ultimate knowledge and rationale behind them to specialist and non-specialist audiences in a clear and unambiguous way.

 

 

 

Learning outcomes (Training objectives)

- To understand how an artificial vision system works.

- To understand the different methods and techniques used in artificial vision to extract information from an image.

- Know the processing stages into which a machine vision system is usually broken down.

- Acquire the ability to apply artificial vision techniques to solve real-world problems.

 

 

Specific objectives stated by the academic staff for academic year 2023-24

No data

 

 

General

Code: 43503
Lecturer responsible:
VICENT FRANCES, JOSE FRANCISCO
Credits ECTS: 4,50
Theoretical credits: 0,90
Practical credits: 0,90
Distance-base hours: 2,70

Departments involved

  • Dept: LANGUAGES AND COMPUTING SYSTEMS
    Area: LANGUAGES AND COMPUTING SYSTEMS
    Theoretical credits: 0,3
    Practical credits: 0,3
  • Dept: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Area: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Theoretical credits: 0,6
    Practical credits: 0,6
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught