المؤلفون: Damien Bouchabou, Juliette Grosset, Sao Mai Nguyen, Christophe Lohr, Xavier Puig

المصدر: Sensors, Vol 23, Iss 17, p 7586 (2023)

مصطلحات موضوعية: smart home, machine learning, home automation, simulator, database, digital twin, Chemical technology, TP1-1185

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1424-8220/23/17/7586; https://doaj.org/toc/1424-8220

URL الوصول: https://doaj.org/article/1b567fd1a3704139a65812d09f10ccff

المؤلفون: Damien Bouchabou, Sao Mai Nguyen, Christophe Lohr, Benoit LeDuc, Ioannis Kanellos

المصدر: Sensors, Vol 21, Iss 18, p 6037 (2021)

مصطلحات موضوعية: survey, human activity recognition, deep learning, smart home, ambient assisting living, taxonomies, Chemical technology, TP1-1185

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1424-8220/21/18/6037; https://doaj.org/toc/1424-8220

URL الوصول: https://doaj.org/article/f25d4a80fa2b47d09103666ab2ad1a16

المؤلفون: Christophe Lohr, Ioannis Kanellos, Sao Mai Nguyen, Damien Bouchabou, Benoit Leduc

المساهمون: Département Informatique (IMT Atlantique - INFO), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Delta Dore SA, Equipe Robot interaction, Ambient system, Machine learning, Behaviour, Optimization (Lab-STICC_RAMBO), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)

المصدر: Communications in Computer and Information Science ISBN: 9789811605741
Li X., Wu M., Chen Z., Zhang L. (eds) Deep Learning for Human Activity Recognition. DL-HAR 2021. Communications in Computer and Information Science, vol 1370. Springer
DL-HAR 2021: 2nd International Workshop on Deep Learning for Human Activity Recognition
DL-HAR 2021: 2nd International Workshop on Deep Learning for Human Activity Recognition, Jan 2021, Yokohama, Japan. pp.111-125, ⟨10.1007/978-981-16-0575-8_9⟩

مصطلحات موضوعية: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Computer science, Feature extraction, Context (language use), 02 engineering and technology, Machine learning, computer.software_genre, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Activity recognition, 020204 information systems, Encoding (memory), FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Redundancy (engineering), Fully Convolutional Network, Smart Homes, Electrical Engineering and Systems Science - Signal Processing, Automatic Features, business.industry, Human Activity Recognition, Artificial Intelligence (cs.AI), Embedding, Domain knowledge, 020201 artificial intelligence & image processing, Artificial intelligence, Word Encoding, business, computer, Word (computer architecture)

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98c683384eafb14a664cad43cce32fdc
https://doi.org/10.1007/978-981-16-0575-8_9