Results 21 to 30 of about 148,198 (270)
SemanticFusion: Dense 3D semantic mapping with convolutional neural networks [PDF]
2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 Ever more robust, accurate and detailed mapping using visual sensing has proven to be an enabling factor for mobile robots across a wide variety of applications. For the next level of robot intelligence and intuitive user interaction, maps need extend beyond geometry and appearence - they need to contain semantics.
McCormac, J +3 more
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Accurate Recognition and Simulation of 3D Visual Image of Aerobics Movement
Complexity, 2020 The structure of the deep artificial neural network is similar to the structure of the biological neural network, which can be well applied to the 3D visual image recognition of aerobics movements.
Wenhua Fan, Hyun Joo Min
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Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 In this paper, we present a novel method for real-time 3D hand pose estimation from single depth images using 3D Convolutional Neural Networks (CNNs). Image-based features extracted by 2D CNNs are not directly suitable for 3D hand pose estimation due to the lack of 3D spatial information.
Liuhao Ge +3 more
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Applied Sciences, 2020 In this paper, a Collision Grid Map (CGM) is proposed by using 3d point cloud data to predict the collision between the cattle and the end effector of the manipulator in the barn environment.
Jun Hyeong Jo, Chang-bae Moon
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Alzheimer’s Detection through 3D Convolutional Neural Networks
The International FLAIRS Conference Proceedings, 2021 To inform a proper diagnosis and understanding of Alzheimer’s Disease (AD), deep learning has emerged as an alternate approach for detecting physical brain changes within magnetic resonance imaging (MRI). The advancement of deep learning within biomedical imaging, particularly in MRI scans, has proven to be an efficient resource for abnormality ...
Ryan Hogan, Christoforos Christoforou
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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 +10 more
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An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Sensors, 2023 Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo +6 more
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iOceanSee: A Novel Scheme for Ocean State Estimation Using 3D Mobile Convolutional Neural Network
IEEE Access, 2020 Ocean state estimation is a basic problem in the field of ocean engineering. Under the trend of data-driven, the development of intelligent ship decision-making, ocean energy system design and other aspects, are inseparable from the estimation of wave ...
Huafeng Wu +7 more
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Shape Carving Methods of Geologic Body Interpretation from Seismic Data Based on Deep Learning
Energies, 2022 The task of seismic data interpretation is a time-consuming and uncertain process. Machine learning tools can help to build a shortcut between raw seismic data and reservoir characteristics of interest. Recently, techniques involving convolutional neural
Sergei Petrov +3 more
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Six-layer Optimized Convolutional Neural Network for Lip Language Identification
EAI Endorsed Transactions on e-Learning, 2021 INTRODUCTION: Lip language is one of the most important communication methods in social life for people with hearing impairment and impaired expression ability.
Yifei Qiao +7 more
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