Multi-Head Attention-Based Framework with Residual Network for Human Action Recognition. [PDF]
Al-Tawil B +3 more
europepmc +1 more source
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Synergistic perspectives—How single‐molecule biophysics complement biochemical understanding
In this review, we discuss how ensemble biochemistry and single‐molecule approaches are complementary, outline commonly used single‐molecule techniques, and illustrate their relevance through two representative case studies: chromatin organization by SMC complexes and pathway choice during DNA double‐strand break repair.
Sara De Bragança +2 more
wiley +1 more source
Semi-supervised action recognition using logit aligned consistency and adaptive negative learning. [PDF]
Zuo F, Xu Y, Wang M.
europepmc +1 more source
Brain-inspired multimodal motion and fine-grained action recognition. [PDF]
Li Y, Yang X, Chen C.
europepmc +1 more source
Lightweight graph convolutional network with multi-attention mechanisms for intelligent action recognition in online physical education. [PDF]
You Y.
europepmc +1 more source
Deep learning-based action recognition for analyzing drug-induced bone remodeling mechanisms. [PDF]
Qinsheng L +3 more
europepmc +1 more source
ADHD detection based on human action recognition. [PDF]
Li Y, Nair R, Naqvi SM.
europepmc +1 more source
Action Recognition in Basketball with Inertial Measurement Unit-Supported Vest. [PDF]
Sonalcan H +3 more
europepmc +1 more source
Related searches:
Actionness-Assisted Recognition of Actions
2015 IEEE International Conference on Computer Vision (ICCV), 2015We elicit from a fundamental definition of action low-level attributes that can reveal agency and intentionality. These descriptors are mainly trajectory-based, measuring sudden changes, temporal synchrony, and repetitiveness. The actionness map can be used to localize actions in a way that is generic across action and agent types. Furthermore, it also
Ye Luo, Loong-Fah Cheong, An Tran
openaire +1 more source

