Results 141 to 150 of about 203,239 (310)

Application of 1D convolutional neural networks for anomaly detection in resistance measurements of railway wheelsets

Pojazdy Szynowe
The article presents the application of convolutional neural networks (CNN) for the classification of electrical resistance measurements of railway wheelsets.
Tomasz Paweł Olejniczak
doaj   +1 more source

Deep Learning as Applied in SAR Target Recognition and Terrain Classification

Leida xuebao, 2017
Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application
Xu Feng, Wang Haipeng, Jin Yaqiu
doaj   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Augmenting convolutional neural networks with kernels inspired by the early visual system [PDF]

, 2022
openEarly neural networks were inspired by biology: the McCulloch-Pitts neuron, the Perceptron and the Neocognitron were all attempting to imitate the functioning of the brain.
ROVOLETTO, MATTEO BRUNO
core  

Boosted Convolutional Neural Networks [PDF]

Procedings of the British Machine Vision Conference 2016, 2016
Mohammad Moghimi, Serge J. Belongie, Mohammad J. Saberian, Jian Yang 0003, Nuno Vasconcelos, Li-Jia Li 0001   +5 more
openaire   +2 more sources

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

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

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

Advanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou, Zhiqiang Chen, Yuanbiao Ma, Zhiqiang Tang, Qianqian Wang   +4 more
wiley   +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, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

A novel online ensemble convolutional neural networks for streaming data

, 2019
In this study, we introduce an online ensemble method based on convolutional neural networks (CNNs) for streaming data. Recent work has shown that a convolution operation has been an effective way to extract features.
Pham, XC, Liew, AWC, Nguyen, TTT
core   +1 more source