Fabio Poiesi

Dr. Fabio Poiesi

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 November 2022 in Applied Sciences
Verified
Journal Article
Open access
PDF file
Zhihan LyuZhihan Lyu
Zhihan Lyu
FPFabio Poiesi
Fabio Poiesi
QDQi Dong
Qi Dong
Jaime LloretJaime Lloret
Jaime Lloret
Houbing Herbert SongHoubing Herbert Song
Houbing Herbert Song
In recent years, gesture recognition and speech recognition, as important input methods in Human–Computer Interaction (HCI), have been widely used in the field of virtual reality. In particular, with the rapid development of deep learning, artificial intelligence, and other computer technologies, gesture recognition and speech recognition have achieved breakthrough research progress. The search platform used in this work is mainly the Google Academic and literature database Web of Science. According to the keywords related to HCI and deep learning, such as “intelligent HCI”, “speech recognition”, “gesture recognition”, and “natural language processing”, nearly 1000 studies were selected. Then, nearly 500 studies of research methods were selected and 100 studies were finally selected as the research content of this work after five years (2019–2022) of year screening. First, the current situation of the HCI intelligent system is analyzed, the realization of gesture interaction and voice interaction in HCI is summarized, and the advantages brought by deep learning are selected for research. Then, the core concepts of gesture interaction are introduced and the progress of gesture recognition and speech recognition interaction is analyzed. Furthermore, the representative applications of gesture recognition and speech recognition interaction are described. Finally, the current HCI in the direction of natural language processing is investigated. The results show that the combination of intelligent HCI and deep learning is deeply applied in gesture recognition, speech recognition, emotion recognition, and intelligent robot direction. A wide variety of recognition methods were proposed in related research fields and verified by experiments. Compared with interactive methods without deep learning, high recognition accuracy was achieved. In Human–Machine Interfaces (HMIs) with voice support, context plays an important role in improving user interfaces. Whether it is voice search, mobile communication, or children’s speech recognition, HCI combined with deep learning can maintain better robustness. The combination of convolutional neural networks and long short-term memory networks can greatly improve the accuracy and precision of action recognition. Therefore, in the future, the application field of HCI will involve more industries and greater prospects are expected.

3 November 2016
Verified
Book Chapter
Closed access
RSRicardo Sanchez-Matilla
Ricardo Sanchez-Matilla
FPFabio Poiesi
Fabio Poiesi
ACAndrea Cavallaro
Andrea Cavallaro

12 September 2024 in Computer Vision and Image Understanding
Verified
Journal Article
Closed access
LZLuca Zanella
Luca Zanella
BLBenedetta Liberatori
Benedetta Liberatori
WMWilli Menapace
Willi Menapace
FPFabio Poiesi
Fabio Poiesi
YWYiming Wang
Yiming Wang
Elisa RicciElisa Ricci
Elisa Ricci

2 November 2022
Verified
Book Chapter
Closed access
PDF file
CSCristiano Saltori
Cristiano Saltori
FGFabio Galasso
Fabio Galasso
Giuseppe FiameniGiuseppe Fiameni
Giuseppe Fiameni
NSNicu Sebe
Nicu Sebe
Elisa RicciElisa Ricci
Elisa Ricci
FPFabio Poiesi
Fabio Poiesi

1 October 2013 in Computer Vision and Image Understanding
Verified
Journal Article
Closed access
FPFabio Poiesi
Fabio Poiesi
RMRiccardo Mazzon
Riccardo Mazzon
ACAndrea Cavallaro
Andrea Cavallaro