Results 101 to 110 of about 143,911 (316)
The framework of the proposed model CNN-Bi-LSTM-ATT.
, 2023 Note: CNN-Bi-LSTM-ATT classifier comprises multiple layers. It starts with an input layer followed by a CNN layer. X1, X2, ⋯, XT represents groups of time series.Three Bi-LSTM layers are then employed to capture past and future information. The attention
Kunliang Xu (17457896) +2 more
core +1 more source
Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot
Advanced Robotics Research, EarlyView.A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini +7 more
wiley +1 more source
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling
Advanced Robotics Research, EarlyView.A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang +5 more
wiley +1 more source
LSTM-based Multi-Step SOC Forecasting of Battery Energy Storage in Grid Ancillary Services
, 2021 Battery energy storage (BES) participation in the grid ancillary services markets is increasing rapidly in recent years. To facilitate optimal participation, the need for accurate BES state-of-charge (SOC) forecasting is indispensable.
Ardiansyah Ardiansyah (11241801) +2 more
core +1 more source
CoRR, 2015 LSTM (Long Short-Term Memory) recurrent neural networks have been highly successful in a number of application areas. This technical report describes the use of the MNIST and UW3 databases for benchmarking LSTM networks and explores the effect of different architectural and hyperparameter choices on performance.
openaire +3 more sources
SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 In crowd scenarios, reliable trajectory prediction of pedestrians requires insightful understanding of their social behaviors. These behaviors have been well investigated by plenty of studies, while it is hard to be fully expressed by hand-craft rules. Recent studies based on LSTM networks have shown great ability to learn social behaviors.
Pu Zhang 0001 +4 more
openaire +3 more sources
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
The initial parameters of several models including the Bi-LSTM-ATT.
, 2023 The initial parameters of several models including the Bi-LSTM-ATT.
Kunliang Xu (17457896) +2 more
core +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source