Results 131 to 140 of about 5,636 (303)

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

FPGA Implementation of Reduced Precision Convolutional Neural Networks

, 2019
With the improvement in processing systems, machine learning applications are finding widespread use in almost all sectors of technology. Image recognition is one application of machine learning which has become widely popular with various ...
Nabil, Muhammad Mohid
core  

Fine-tuned convolutional neural nets for cardiac MRI acquisition plane recognition

, 2015
This is an electronic version of an article published inComputer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualizationon 13 August 2015, by Taylor & Francis, DOI: 10.1080/21681163.2015.1061448.Available online at: http://www ...
Margeta, Jan, Ayache, Nicholas, Criminisi, Antonio, Lee, Daniel C., Cabrera Lozoya, Rocio   +4 more
core   +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, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

Application of wavelets and artificial neural network for indoor optical wireless communication systems

This study investigates the use of error control code, discrete wavelet transform (DWT) and artificial neural network (ANN) to improve the link performance of an indoor optical wireless communication in a physical channel.
Rajbhandari, Sujan
core  

Transfer learning techniques for deep neural nets

, 2010
Inductive learners seek meaningful features within raw input. Their purpose is to accurately categorize, explain or extrapolate from this input. Relevant features for one task are frequently relevant for related tasks.
Gutstein, Steven Michael, Gutstein, Steven M.   +1 more
core  

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, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Recognition of European mammals and birds in camera trap images using deep neural networks

IET Computer Vision
Most machine learning methods for animal recognition in camera trap images are limited to mammal identification and group birds into a single class. Machine learning methods for visually discriminating birds, in turn, cannot discriminate between mammals ...
Daniel Schneider, Kim Lindner, Markus Vogelbacher, Hicham Bellafkir, Nina Farwig, Bernd Freisleben   +5 more
doaj   +1 more source

Deep learning of reaction properties via graph-convolutional neural nets

, 2023
Machine learning models are very successful in predicting various chemical properties. Graph-convolutional neural networks (GCNNs) are routinely used for the prediction of molecular properties, but their application to chemical reactions is largely ...
Heid, Esther Carina; orcid:
core