Educational guide
IDENTIFYING DATA 2024_25
Subject OBJECT RECOGNITION Code 01751009
Study programme
1751 - M.U.ROBOTICA E INTELIGENCIA ARTIFICIAL
Descriptors Credit. Type Year Period
3 Compulsory First Second
Language
Castellano
Prerequisites
Department ING.MECANICA,INFORMAT.AEROESP.
Coordinador
RIEGO DEL CASTILLO , VIRGINIA
E-mail vriec@unileon.es
lferr@unileon.es
Lecturers
FERNANDEZ ROBLES , LAURA
RIEGO DEL CASTILLO , VIRGINIA
Web http://agora.unileon.es
General description
Tribunales de RevisiĆ³n
Tribunal titular
Cargo Departamento Profesor
Presidente ING.MECANICA,INFORMAT.AEROESP. MATELLAN OLIVERA , VICENTE
Secretario ING.MECANICA,INFORMAT.AEROESP. PANIZO ALONSO , LUIS
Vocal CONDE GONZALEZ , MIGUEL ANGEL
Tribunal suplente
Cargo Departamento Profesor
Presidente MATEMATICAS GARCIA SIERRA , JUAN FELIPE
Secretario ING.MECANICA,INFORMAT.AEROESP. RODRIGUEZ LERA , FRANCISCO JAVIER
Vocal ING.MECANICA,INFORMAT.AEROESP. FERNANDEZ LLAMAS , CAMINO


Topic Sub-topic
I. Introduction 1. Introduction to Object Recognition
II. Object Detection 1. Object Location
2. Object Detection
3. Object Tracking

Methodologies  ::  Tests
  Class hours Hours outside the classroom Total hours
Practicals using information and communication technologies (ICTs) in computer rooms 15 30 45
 
Assignments 3 10 13
 
Lecture 10 5 15
 
Objective short-answer tests 2 0 2
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies   ::  
  Description
Practicals using information and communication technologies (ICTs) in computer rooms Programs will be developed with different models for object recognition in the field of robotics using computer vision techniques.
Assignments Different works will be carried out applying the concepts seen in theory and practice to real cases in the field of robotics.
Lecture The different existing theoretical concepts that allow solving object recognition problems in the field of robotics will be presented.

 
Lecture
Practicals using information and communication technologies (ICTs) in computer rooms
Assignments
Description
To solve the doubts that arise when solving problems solved in class or proposed (both theory and practical), it is recommended to use the doubts forum or request a tutorial with the professor.

  Description Qualification
Lecture A test will be given to evaluate the concepts seen in the theory sessions 20%
Practicals using information and communication technologies (ICTs) in computer rooms Different practical exercises will be delivered where the concepts seen in the practical sessions will be developed 60 - 80%
Assignments Different works will be carried out applying the concepts seen in the resolution of real problems in the field of robotics. 0 - 20%
 
Other comments and second call

1. BEHAVIOR IN CLASS:

In the development of the subject, you must avoid behaviors that in the opinion of the teacher are undesirable, being able to be expelled from the activity otherwise. 

2. BEHAVIOR IN THE EXAM

The work submitted may be reviewed with an anti-plagiarism software that can perform checks between the work submitted in the current and previous call and against external sources. If plagiarism is detected, the work will be graded as failed. During the evaluation tests it will not be possible to use electronic resources (calculators, tablets, phones, computers, etc.), except for those tests that under the express indication of the teacher require the use of any of these resources. In case of any irregularity occurring during the celebration of the corresponding exam or evaluation test, the provisions of the internal regulations of the ULE included in the document "Guidelines for action in cases of plagiarism, copying or fraud in exams or evaluation tests" (Approved Standing Committee of the Governing Council 29/01/2015) will be taken into account.

3. FIRST CALL

Passing the course will require passing with a minimum grade in each of the parts. Unless expressly indicated during the development of the course, this minimum grade will be:

  • Minimum for the theory part: 4.0
  • Minimum for the practices and deliveries made: 4.0

4. SECOND CALL

In the second call there will be an evaluation test of the parts failed in the first call


Basic Szeliski, Computer Vision: Algorithms And Applications, Springer, 2022
Elgendy, Deep Learning for Vision Systems, Manning, 2020
V Kishore Ayyadevara, Yeshwanth Reddy , Modern Computer Vision with PyTorch, Packt, 2020
Sandipan Dey, Python Image Processing cookbook, Packt, 2020

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