Results 91 to 100 of about 8,410,900 (380)
Learning 3D Skeletal Representation From Transformer for Action Recognition
IEEE Access, 2022 Skeleton-based human action recognition has attracted significant interest due to its simplicity and good accuracy. Diverse end-to-end trainable frameworks based on skeletal representation have been proposed so far to map the representation to human ...
Junuk Cha +5 more
doaj +1 more source
Action-Attending Graphic Neural Network
, 2017 The motion analysis of human skeletons is crucial for human action recognition, which is one of the most active topics in computer vision. In this paper, we propose a fully end-to-end action-attending graphic neural network (A$^2$GNN) for skeleton-based ...
Cui, Zhen +5 more
core +1 more source
Intravitreal GD2‐Specific Chimeric Antigen Receptor T‐Cell Therapy for Refractory Retinoblastoma
Pediatric Blood &Cancer, EarlyView.ABSTRACT Effective treatments for advanced, treatment‐resistant retinoblastoma (RB) remain limited. GD2‐specific chimeric antigen receptor (CAR) T cells show potent antitumor activity with minimal toxicity but have not previously been evaluated in RB.
Subongkoch Subhadhirasakul +13 more
wiley +1 more source
Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition [PDF]
, 2021 Liang Xu +3 more
openalex +1 more source
Differential Recurrent Neural Networks for Action Recognition
, 2015 The long short-term memory (LSTM) neural network is capable of processing complex sequential information since it utilizes special gating schemes for learning representations from long input sequences.
Qi, Guo-Jun +2 more
core +1 more source
Instant Action Recognition [PDF]
, 2009 In this paper, we present an efficient system for action recognition from very short sequences. For action recognition typically appearance and/or motion information of an action is analyzed using a large number of frames. This is a limitation if very fast actions (e.g., in sport analysis) have to be analyzed.
Thomas Mauthner +2 more
openaire +1 more source
Model recommendation for action recognition [PDF]
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012 Simply choosing one model out of a large set of possibilities for a given vision task is a surprisingly difficult problem, especially if there is limited evaluation data with which to distinguish among models, such as when choosing the best “walk” action classifier from a large pool of classifiers tuned for different viewing angles, lighting conditions,
Matikainen, Pyry +2 more
openaire +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Nurses are central to cancer care for children and adolescents, yet no comprehensive synthesis has defined essential core competencies for pediatric oncology nursing (PON) practice internationally, particularly in Latin America and the Caribbean (LAC).
Luís Carlos Lopes‐Júnior +7 more
wiley +1 more source
Pose for Action - Action for Pose
, 2017 In this work we propose to utilize information about human actions to improve pose estimation in monocular videos. To this end, we present a pictorial structure model that exploits high-level information about activities to incorporate higher-order part ...
Gall, Juergen +2 more
core +1 more source
Temporal Segment Networks for Action Recognition in Videos [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 We present a general and flexible video-level framework for learning action models in videos. This method, called temporal segment network (TSN), aims to model long-range temporal structure with a new segment-based sampling and aggregation scheme.
Limin Wang +6 more
semanticscholar +1 more source