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Semi-supervised deep networks for plasma state identification
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$a 10.1088/1361-6587/ac9926 $2 DOI 101 0-
$a eng 102 $a GB 200 1-
$a Semi-supervised deep networks for plasma state identification 215 $a 16 s. 463 -1
$1 001 cav_un_epca*0257477 $1 011 $a 0741-3335 $e 1361-6587 $1 200 1 $a Plasma Physics and Controlled Fusion $v Roč. 64, č. 12 (2022) $1 210 $c Institute of Physics Publishing 608 $a Article 610 $a plasma 610 $a neural networks 610 $a semi-supervised learning 610 $a classification 700 -1
$3 cav_un_auth*0447438 $a Zorek $b M. $y CZ $4 070 $z K $q Czech Tech Univ, Dept Comp Sci, FEE, Prague, Czech Republic, 701 -1
$3 cav_un_auth*0447439 $a Škvára $b V. $y CZ $4 070 $q Czech Tech Univ, Dept Comp Sci, FEE, Prague, Czech Republic, 701 -1
$3 cav_un_auth*0239629 $a Smidl $b L. $y CZ $q Czech Tech Univ, Dept Comp Sci, FEE, Prague, Czech Republic, 701 -1
$3 cav_un_auth*0307300 $a Pevný $b T. $y CZ $q Czech Tech Univ, Dept Comp Sci, FEE, Prague, Czech Republic, 701 -1
$3 cav_un_auth*0257948 $a Seidl $b Jakub $p UFP-V $i Tokamak $j Tokamak $k TOK $l TOK $y CZ $q CAS, Inst Plasma Phys, Prague, Czech Republic, $T Ústav fyziky plazmatu AV ČR, v. v. i. 701 -1
$3 cav_un_auth*0346034 $a Grover $b Ondřej $p UFP-V $i Tokamak $j Tokamak $k TOK $l TOK $y CZ $q CAS, Inst Plasma Phys, Prague, Czech Republic, $T Ústav fyziky plazmatu AV ČR, v. v. i. 856 $u https://iopscience.iop.org/article/10.1088/1361-6587/ac9926 $9 RIV
Number of the records: 1