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@article{CSIS_2022_19_3_a4, author = {Matija Ter\v{s}ek and Ma\v{s}a Kljun and Peter Peer and \v{Z}iga Emer\v{s}i\v{c}}, title = {Re-evaluation of the {CNN-based} state-of-the-art crowd-counting methods with enhancements}, journal = {Computer Science and Information Systems}, publisher = {mathdoc}, volume = {19}, number = {3}, year = {2022}, url = {http://geodesic.mathdoc.fr/item/CSIS_2022_19_3_a4/} }
TY - JOUR AU - Matija Teršek AU - Maša Kljun AU - Peter Peer AU - Žiga Emeršič TI - Re-evaluation of the CNN-based state-of-the-art crowd-counting methods with enhancements JO - Computer Science and Information Systems PY - 2022 VL - 19 IS - 3 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/CSIS_2022_19_3_a4/ ID - CSIS_2022_19_3_a4 ER -
%0 Journal Article %A Matija Teršek %A Maša Kljun %A Peter Peer %A Žiga Emeršič %T Re-evaluation of the CNN-based state-of-the-art crowd-counting methods with enhancements %J Computer Science and Information Systems %D 2022 %V 19 %N 3 %I mathdoc %U http://geodesic.mathdoc.fr/item/CSIS_2022_19_3_a4/ %F CSIS_2022_19_3_a4
Matija Teršek; Maša Kljun; Peter Peer; Žiga Emeršič. Re-evaluation of the CNN-based state-of-the-art crowd-counting methods with enhancements. Computer Science and Information Systems, Tome 19 (2022) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2022_19_3_a4/