Results 61 to 70 of about 89,843 (211)

Generalized Sparse Convolutional Neural Networks for Semantic Segmentation of Point Clouds Derived from Tri-Stereo Satellite Imagery

Remote Sensing, 2020
We studied the applicability of point clouds derived from tri-stereo satellite imagery for semantic segmentation for generalized sparse convolutional neural networks by the example of an Austrian study area.
Stefan Bachhofner, Ana-Maria Loghin, Johannes Otepka, Norbert Pfeifer, Michael Hornacek, Andrea Siposova, Niklas Schmidinger, Kurt Hornik, Nikolaus Schiller, Olaf Kähler, Ronald Hochreiter   +10 more
doaj   +1 more source

Multilevel Embedding and Dropout for Improved 3D Object Detection in Autonomous Driving Systems

Advanced Robotics Research, EarlyView.
A plug‐in framework for RoI‐based 3D object detectors exploits previously untapped multi‐level information within RoI features. Its novel multi‐level embedding and dropout strategy enables the detection head to generate predictions at different feature levels.
Xiaohu Lu, Hayder Radha
wiley   +1 more source

Malaria parasite segmentation using U-Net: Comparative study of loss functions

Communications in Science and Technology, 2019
The convolutional neural network is commonly used for classification. However, convolutional networks can also be used for semantic segmentation using the fully convolutional network approach.
Julisa Bana Abraham
doaj   +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

Deep Learning-Based Approaches for Brain Tumour Segmentation and Classification

European Medical Journal
Brain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery.
Vidya Baiju, Akshitha J, Namasiyava Naveen S   +2 more
doaj   +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

DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

EURASIP Journal on Image and Video Processing, 2019
Recent state-of-the-art methods for skin lesion segmentation are based on convolutional neural networks (CNNs). Even though these CNN-based segmentation approaches are accurate, they are computationally expensive.
Saleh Baghersalimi, Behzad Bozorgtabar, Philippe Schmid-Saugeon, Hazım Kemal Ekenel, Jean-Philippe Thiran   +4 more
doaj   +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

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

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, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 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