倔强一点
发表于 2025-3-30 09:57:48
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aspersion
发表于 2025-3-30 15:57:16
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Medicaid
发表于 2025-3-30 20:14:54
Learning and Recognizing Routines and Activities in SOFiA, is doing. To this aim we developed a system called WoMan that, using a process mining approach, is able to incrementally learn user’s activities and daily routines as workflow models. In order to test its efficacy in a real-world setting, we set up a smart office environment, SOFiA, equipped with a
ALOFT
发表于 2025-3-31 00:16:02
On-line Context Aware Physical Activity Recognition from the Accelerometer and Audio Sensors of Smauser (health monitoring, fitness, context-awareness) as well as for third party applications and social network (performance sharing, profiling). Most of the research effort has been focused on direct recognition from accelerometer sensors and few studies have integrated the audio channel in their m
Nonthreatening
发表于 2025-3-31 01:12:26
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accrete
发表于 2025-3-31 07:14:36
Developing a Face Monitoring Robot for a Desk Worker,ect to search for the desk worker and adjusts its position for monitoring. The monitoring is based on incremental clustering of the faces. Our experiments revealed that not only Animation Units (AUs) features, which represent deviations from the neutral face, but also the pitch angle of the face nor
无情
发表于 2025-3-31 11:27:31
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discord
发表于 2025-3-31 13:50:00
Ambient Intelligence978-3-319-14112-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
慢慢啃
发表于 2025-3-31 20:06:03
https://doi.org/10.1007/978-3-642-94141-2ts and the Internet of Things, showing how it can be used to effect discrete control in smart home environments by mediating and adapting generic rules through finite-state-machine models drawn from a domain ontology, representing observable & controllable “things” and space entities in this infrastructure.
一再困扰
发表于 2025-3-31 22:53:34
Acta Neurochirurgica Supplementtems for the elderly and energy consumption optimization. Sensing the environmental state via different sensors is the first and crucial component of every ambient intelligent system. In this work we investigate the use of environmental sounds for touch-free audio-based device recognition in a home