IMT4392 - Deep Learning for Visual Computing

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Vurderingsordning: Project report and presentation of the project work
Karakter: Bokstavkarakterer

Vurdering Vekting Varighet Delkarakter Hjelpemidler
Project report and presentation of the project work 100/100

Faglig innhold

- Introduction to deep learning (DL) - Deep neural networks (DNN) - Convolutional neural network (CNN) - Recurrent neural network (RNN) - Introduction to visual computing - Still-image and video processing - Enhancement, filtering and segmentation - Selected case studies on DL for visual computing


On successful completion of the module, students will be able to - Possess advanced knowledge within the area of Deep learning for visual computing. Understand the meaning of concepts such as Multi-layer perceptron, Dropout, Convolutional networks. - Possess specialized insight and good understanding of the research frontier of Deep learning techniques and algorithms for visual computing applications.

Skills and general competence: - Be able to use relevant and suitable methods when carrying out further research and development activities in the area of Deep learning for visual computing - Be able to critically review relevant literature when solving the assigned problem or topic. - Is able to communicate academic issues, analysis, and conclusions, with specialists in the field, in oral and written forms - Is experienced in acquiring new knowledge and skills in a self-directed manner - Develop a course project based on an application scenario and implement several of the algorithms to solve practical problems. The students will also enhance their programming skills in Python and Tensorflow.

Læringsformer og aktiviteter

Lectures, exercises, self-study, presentation and obligatory course project. This course will focus on practical implementation of Deep Learning for visual computing.

Mer om vurdering

Project report and presentation of the project work


There is no required textbook and students should be able to learn everything from the suggested materials and mentoring during the course project.

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Versjon: 1
Studiepoeng:  7.5 SP
Studienivå: Høyere grads nivå


Termin nr.: 1
Undervises:  HØST 2023

Undervisningsspråk: Engelsk

Sted: Gjøvik

  • Informatikk

Ansvarlig enhet
Institutt for datateknologi og informatikk


Vurderingsordning: Project report and presentation of the project work

Termin Statuskode Vurdering Vekting Hjelpemidler Dato Tid Eksamens- system Rom *
Høst ORD Project report and presentation of the project work 100/100





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