Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Ammar, Wiem Haj"'
Autor:
Ammar, Wiem Haj, Boujnah, Aicha, Baron, Antoine, Boubaker, Aimen, Kalboussi, Adel, Lmimouni, Kamal, Pecqueur, Sebastien
Identifying relevant machine-learning features for multi-sensing platforms is both an applicative limitation to recognize environments and a necessity to interpret the physical relevance of transducers' complementarity in their information processing
Externí odkaz:
http://arxiv.org/abs/2401.00684
Autor:
Ammar, Wiem Haj, Boujnah, Aicha, Boubaker, Aimen, Kalboussi, Adel, Lmimouni, Kamal, Pecqueur, Sébastien
Multivariate data analysis and machine-learning classification become popular tools to extract features without physical models for complex environments recognition. For electronic noses, time sampling over multiple sensors must be a fair compromise
Externí odkaz:
http://arxiv.org/abs/2308.12623