Results 71 to 80 of about 4,047,749 (292)

Customizable Piezo‐Transmittance‐Based Multiaxial Force Sensor With Deep‐Learning‐Assisted Sensing

Advanced Materials Technologies, EarlyView.
Development of a soft tri‐axis piezo‐transmittance sensor with integrated LEDs and photodiodes enables multidirectional force sensing through deformation‐induced optical modulation. A tailored 1D convolutional neural network provides real‐time force direction and intensity prediction, achieving 99.6% classification accuracy and a mean squared error of ...
Filippo Peruzzi, Osman Gul, Wonhee Lee, Seokjoo Cho, Yong‐Jin Yoon, Paola Saccomandi, Inkyu Park   +6 more
wiley   +1 more source

Visualizing Convolutional Neural Networks with Virtual Reality [PDF]

, 2019
Software systems and components are increasingly based on machine learning methods, such as Convolutional Neural Networks (CNNs). Thus, there is a growing need for common programmers and machine learning newcomers to understand the general functioning of
Meissler, Nadine, Wohlan, Annika, Nico Hochgeschwender, Hochgeschwender, Nico, Nadine Meissler, Annika Wohlan   +5 more
core   +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

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, Elena Adelucci, Stefano Scatigna, Lorenzo Pugi, Alice Bruni, Benedetta Carotenuto, Chiara Pecini, Filippo Cavallo   +7 more
wiley   +1 more source

Learning shape correspondence with anisotropic convolutional neural networks [PDF]

, 2016
Convolutional neural networks have achieved extraordinary results in many computer vision and pattern recognition applications; however, their adoption in the computer graphics and geometry processing communities is limited due to the non-Euclidean ...
Rodolà, Emanuele, Bronstein, Michael, Masci, Jonathan, Boscaini, Davide, Bronstein, Michael M.   +4 more
core  

Convolutional neural networks with dynamic regularization

, 2020
Regularization is commonly used for alleviating overfitting in machine learning. For convolutional neural networks (CNNs), regularization methods, such as DropBlock and Shake-Shake, have illustrated the improvement in the generalization performance ...
Wang, Yi, Chau, Lap-Pui, Bian, Zhen-Peng, Hou, Junhui   +3 more
core   +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

Fractal Neural Network Approach for Analyzing Satellite Images

Applied Artificial Intelligence
Satellites play a critical role in modern technology by providing images for various applications, such as detecting infrastructure and assessing environmental impacts. The author’s work investigates the application of Fractal Neural Networks (FractalNet)
Volodymyr Shymanskyi, Oleh Ratinskiy, Nataliya Shakhovska   +2 more
doaj   +1 more source

CNN-MGP: Convolutional Neural Networks for Metagenomics Gene Prediction [PDF]

Interdisciplinary Sciences: Computational Life Sciences, 2018
Accurate gene prediction in metagenomics fragments is a computationally challenging task due to the short-read length, incomplete, and fragmented nature of the data. Most gene-prediction programs are based on extracting a large number of features and then applying statistical approaches or supervised classification approaches to predict genes.
Amani Al-Ajlan, Achraf El Allali
openaire   +2 more sources

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