@inproceedings{Fojtu-POSTER-2013,
  IS = { zkontrolovano 15 Jan 2014 },
  UPDATE  = { 2013-08-02 },
   author    = {Fojt{\r u}, {\v S}imon},
   language  = {English},
   title     = {Domain Adaptation for Sequential Detection},
   year      = {2013},
   month     = {May},
   pages     = {1--5},
   editor    = {Libor Husn{\' i}k},
   booktitle = {17th International Student Conference on Electrical Engineering},
   publisher = {Czech Technical University in Prague},
   location  = {Prague, Czech Republic},
   address   = {Technick{\' a} 2, Prague, Czech Republic},
   isbn      = {978-80-01-05242-6},
   book_pages= {705},
   annote    = {We propose a domain adaptation method for sequential
     decision-making process, which is suitable for real-time
     processing. The work is motivated by applications in
     surveillance, where detectors must be adapted to new observation
     conditions. We address the situation, where the new observation
     is related to the previous observation by a parametric
     transformation. We propose a learning procedure, which reveals
     the hidden transformation between the old and new data. The
     transformation essentially allows to transfer the knowledge from
     the old data to the new one.  We show that our method can achieve
     a 60% speedup in the training w.r.t. the baseline WaldBoost
     algorithm while outperforming it in precision.},
   keywords   = {domain adaptation, knowledge transfer, sequential decision},
   authorship = {100},
   project    = {SGS12/187/OHK3/3T/13},
   psurl      = {PDF },
   www        = {ftp://cmp.felk.cvut.cz/pub/cmp/articles/fojtusim/Fojtu-POSTER-2013.pdf},
   day        = { 16 },
   venue      = { Prague, Czech Republic },
   organization = { Czech Technical University in Prague, Czech Republic },
   acceptance_ratio = {0.93},
   note       = {CD-ROM, IC05},
}