文献
J-GLOBAL ID:202202249159505639
整理番号:22A1093416
一般的な金属酸化物センサデータセットにおけるドリフトはガス分類ベンチマークの限界を明らかにする【JST・京大機械翻訳】
Drift in a popular metal oxide sensor dataset reveals limitations for gas classification benchmarks
著者 (8件):
Dennler Nik
(UH Biocomputation Research Group, Centre for Computer Science and Informatics Research, University of Hertfordshire, Hatfield, United Kingdom)
,
Dennler Nik
(International Centre for Neuromorphic Systems, Western Sydney University, Sydney, Australia)
,
Rastogi Shavika
(UH Biocomputation Research Group, Centre for Computer Science and Informatics Research, University of Hertfordshire, Hatfield, United Kingdom)
,
Rastogi Shavika
(International Centre for Neuromorphic Systems, Western Sydney University, Sydney, Australia)
,
Fonollosa Jordi
(Departament d′Enginyeria de Sistemes, Automatica i Informatica Industrial, Universitat Politecnica de Catalunya, Barcelona, Spain)
,
Fonollosa Jordi
(Institut de Recerca Sant Joan de Deu, Esplugues de Llobregat, Spain)
,
van Schaik Andre
(International Centre for Neuromorphic Systems, Western Sydney University, Sydney, Australia)
,
Schmuker Michael
(UH Biocomputation Research Group, Centre for Computer Science and Informatics Research, University of Hertfordshire, Hatfield, United Kingdom)
資料名:
Sensors and Actuators. B. Chemical
(Sensors and Actuators. B. Chemical)
巻:
361
ページ:
Null
発行年:
2022年
JST資料番号:
T0967A
ISSN:
0925-4005
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)