Zobrazeno 1 - 10
of 1 199
pro vyhledávání: '"intention recognition"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract The rapid advancement of artificial intelligence has significantly expanded the role of service robots in everyday life. This expansion necessitates the accurate recognition and prediction of human intentions to provide timely and appropriat
Externí odkaz:
https://doaj.org/article/911849af24d84f88aefed78fe127adac
Publikováno v:
工程科学学报, Vol 46, Iss 10, Pp 1845-1855 (2024)
In recent years, with the rapid development of big data and artificial intelligence technology, data-driven automatic driving vehicle lane change intention recognition has become an active research area in the transportation field. Numerous studies h
Externí odkaz:
https://doaj.org/article/f9c6dfd932f54e63bcb178fc0ee59f25
Publikováno v:
Tongxin xuebao, Vol 45, Pp 149-165 (2024)
By transforming time series into images, a robust and transferable tactical intent recognition framework was proposed, which integrated curve filtering technology and the EfficientNetV2 image recognition network. Curve filtering technology effectivel
Externí odkaz:
https://doaj.org/article/f403c792c0b541b4a2786607b4d29d0d
Autor:
Yi Chen, Zhe Tao, Ruizhe Chang, Yudong Cao, Guolin Yun, Weihua Li, Shiwu Zhang, Shuaishuai Sun
Publikováno v:
Advanced Science, Vol 11, Iss 37, Pp n/a-n/a (2024)
Abstract Prosthetic hands play a vital role in restoring forearm functionality for patients who have suffered hand loss or deformity. The hand gesture intention recognition system serves as a critical component within the prosthetic hand system. Howe
Externí odkaz:
https://doaj.org/article/16501ecbcd6f4b9286fd177fbb71b10d
Publikováno v:
IEEE Access, Vol 12, Pp 44998-45010 (2024)
Air formation is a common style of air combat, which demonstrates a high degree of flexibility and strategic value in complex battlefield environments. The activity state of air formation is the result of the intertwining of time domain and air domai
Externí odkaz:
https://doaj.org/article/967cdfd7c5e04006baba51eb19a26b89
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)
Abstract To address the challenges posed by imbalanced and limited battlefield data, which typically results in complex models prone to overfitting during training, we introduce a novel diffusion model grounded in Wasserstein distance (WDiffusion) ta
Externí odkaz:
https://doaj.org/article/8f18683b005343978bd4fdc4740b47a7
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 46, Iss 3, Pp 75-85 (2024)
In modern military warfare, the pattern of air-ground coordination with multi-formation has become more and more important. However, the existing target intention recognition methods are effective for single formation, but lack of effective solutions
Externí odkaz:
https://doaj.org/article/b4da1a935fa549c2ac4113b18f231cb7
Publikováno v:
IEEE Access, Vol 12, Pp 112074-112084 (2024)
To address the issue of model performance degradation in combat intention recognition caused by the long-tailed distribution of battlefield data and the neglect of the spatial dimension information of multivariate time series data, this paper propose
Externí odkaz:
https://doaj.org/article/65fe79be8c60489cb9bd778c76aaf379
Autor:
Jaewon Byun, Keehoon Kim
Publikováno v:
IEEE Access, Vol 12, Pp 66100-66109 (2024)
This paper discusses the benefits of employing surface electromyography (sEMG) signals for power-assisted control to recognize human motion intention swiftly and efficiently from an agility perspective. A majority of power-assisted control systems us
Externí odkaz:
https://doaj.org/article/0aa8a4baa553461c9020696261bfcbf5
Publikováno v:
IEEE Access, Vol 12, Pp 31685-31696 (2024)
Intent recognition in few-shot scenarios is a hot research topic in natural language understanding tasks. Aiming at the problems of insufficient consideration of fine-grained features of the text and insufficient training of features in the process o
Externí odkaz:
https://doaj.org/article/3e286d5cbca5490abf786504dde8a94e