Zobrazeno 1 - 10
of 496
pro vyhledávání: '"Sandeep, K. S."'
Control affine assumptions, human inputs are external disturbances, in certified safe controller synthesis approaches are frequently violated in operational deployment under causal human actions. This paper takes a human-in-the-loop human-in-the-plan
Externí odkaz:
http://arxiv.org/abs/2409.03780
We explore the usage of large language models (LLM) in human-in-the-loop human-in-the-plant cyber-physical systems (CPS) to translate a high-level prompt into a personalized plan of actions, and subsequently convert that plan into a grounded inferenc
Externí odkaz:
http://arxiv.org/abs/2405.11458
We evaluated whether integration of expert guidance on seizure onset zone (SOZ) identification from resting state functional MRI (rs-fMRI) connectomics combined with deep learning (DL) techniques enhances the SOZ delineation in patients with refracto
Externí odkaz:
http://arxiv.org/abs/2312.09360
Non-linearities in simulation arise from the time variance in wireless mobile networks when integrated with human in the loop, human in the plant (HIL-HIP) physical systems under dynamic contexts, leading to simulation slowdown. Time variance is hand
Externí odkaz:
http://arxiv.org/abs/2309.06558
Knowledge transfer across sensing technology is a novel concept that has been recently explored in many application domains, including gesture-based human computer interaction. The main aim is to gather semantic or data driven information from a sour
Externí odkaz:
http://arxiv.org/abs/2306.15114
Surgical disconnection of Seizure Onset Zones (SOZs) at an early age is an effective treatment for Pharmaco-Resistant Epilepsy (PRE). Pre-surgical localization of SOZs with intra-cranial EEG (iEEG) requires safe and effective depth electrode placemen
Externí odkaz:
http://arxiv.org/abs/2306.05572
Autor:
Hossain, Sameena, Kamboj, Payal, Maity, Aranyak, Azuma, Tamiko, Banerjee, Ayan, Gupta, Sandeep K. S.
Gestures that share similarities in their forms and are related in their meanings, should be easier for learners to recognize and incorporate into their existing lexicon. In that regard, to be more readily accepted as standard by the Deaf and Hard of
Externí odkaz:
http://arxiv.org/abs/2306.01944
Publikováno v:
Frontiers in Neurology, Vol 14 (2024)
We evaluated whether integration of expert guidance on seizure onset zone (SOZ) identification from resting state functional MRI (rs-fMRI) connectomics combined with deep learning (DL) techniques enhances the SOZ delineation in patients with refracto
Externí odkaz:
https://doaj.org/article/ca7b3800712347d691986f0bb66bc78e
