Results 121 to 130 of about 8,090,223 (299)
Emotion Recognition from the perspective of Activity Recognition
CoRRApplications of an efficient emotion recognition system can be found in several domains such as medicine, driver fatigue surveillance, social robotics, and human-computer interaction. Appraising human emotional states, behaviors, and reactions displayed in real-world settings can be accomplished using latent continuous dimensions.
Savinay Nagendra, Prapti Panigrahi
openaire +2 more sources
Activity recognition using Grey-Markov model [PDF]
, 2011 Activity Recognition (AR) is a process of identifying actions and goals of one or more agents of interest. AR techniques have been applied to both large and small scale activity identification.
NC DOCKS at Western Carolina University +1 more
core
, 2022 Wearable sensors potentially enable for a better and unobtrusive recognition of human activity and the state of rest, sleep, stress and drive the ongoing trend of the quantified self-movement.
core +1 more source
FEBS Letters, EarlyView.Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
The human gut microbiome across the life course
FEBS Letters, EarlyView.Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
wiley +1 more source
Active transfer learning for activity recognition.
, 2016 We examine activity recognition from accelerometers, which provides at least two major challenges for machine learning. Firstly, the deployment context is likely to differ from the learning context. Secondly, accurate labelling of training data is time-consuming and error-prone. This calls for a combination of active and transfer learning.
Diethe, Tom, Twomey, Niall, Flach, Peter
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Sensor-Based Activity Recognition and Artificial Intelligence
This book constitutes the proceedings of the 9th International Workshop on Sensor-Based Activity Recognition and Artificial Intelligence, iWOAR 2024, held in Potsdam, Germany, during September 26–27, 2024.
core +1 more source
FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
Feature learning via partial differential equation with applications to face recognition
, 2017 Feature learning is a critical step in pattern recognition, such as image classification. However, most of the existing methods cannot extract features that are discriminative and at the same time invariant under some transforms.
Fang, Cong +7 more
core +1 more source
FEBS Letters, EarlyView.This study reveals that the small GTPase Rab14 is necessary for human papillomavirus (HPV) infection and plays an essential role in the transport of virions to the trans‐Golgi network (TGN). HPV in the early endosome (EE), which harbors GTP‐bound Rab14, is transported to the TGN through the switch of Rab14 from its GTP‐bound to GDP‐bound form.
Yoshiyuki Ishii, Iwao Kukimoto
wiley +1 more source