Ostatnia aktualizacja:
September 25. 2017 20:32:33
Aktualności / News > Dydaktyka / Teaching > Historia / History > Data Compression, winter 12/13

Data Compression, winter 12/13


Lecture is given by Prof. Irmina Herburt.

Results

Projects - bibliography

  1. Yimin C., Yixiao W., Qibin S., Longxiang S.: Digital Image Compression Using a Genetic Algorithm. 
    Real-time Imaging 5 (1999) pp. 379-383
  2. Alsing R., Genetic Programming: Evolution of Mona Lisa (http://rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/)
  3. Mitra SK, Murthy CA, Kundu MK. Technique for fractal image compression using genetic algorithm. IEE Trans. Image Processing 7 (1998) 586-593
  4. Wu MS, Jeng JH, Hsieh JG. Schema genetic algorithm for fractal image compression. Engineering Applications of Artificial Intelligence 20 (2007), pp. 531-538
  5. Jiang J. Image compression with neural networks. A survey. Signal Processing: Image Communication 14 (1999), pp. 737-760
  6. Costa S., Fiori S. Image compression using principal component neural networks. Image and Vision Computing 19 (2001). pp. 649-668
  7. Amerijckx C, Verleysen M, Thissen P, Legat JD. Image compression by self-organized Kohonen map. IEEE Transactions on Neural Networks 9 (1998) pp. 503-507

Deadlines:

17.10.2012 Groups and topics
31.10.2012 Functional Documentation
09.01.2013 Application
16.01.2013 Final Presentation (proposal)
pre-last lecture - presentation

Project is written in pairs or groups of three (bigger groups will have bigger projects).

You should implement a given algorithm and test it on benchmark images.

Marks:

25% Functional Documentation
40% Application
35% Final Presentation

Late submissions: -10% of total grade for every started week after the deadline