Results 81 to 90 of about 6,781,577 (302)
Lung Nodule Classification Based on 3D Convolutional Neural Network
Journal of Harbin University of Science and Technology, 2021 In order to improve the classification accuracy of ground glass nodules that are difficult to segment and diagnose and at the same time，the VGG16 network structure has deep convolutional layers and many parameters，A 3D deep convolutional neural network ...
WANG Wei-bing +3 more
doaj +1 more source
ST-CNN: Spatial-Temporal Convolutional Neural Network for crowd counting in videos
, 2019 The task of crowd counting and density maps estimating from videos is challenging due to severe occlusions, scene perspective distortions and diverse crowd distributions.
Gao, Y, Han, J, Zhang, B, Miao, Y
core +1 more source
Advances in Bio‐Integrated Edge Computing Systems for Smart and Connected Health
Advanced Materials, EarlyView.This review explores advances in bio‐integrated edge computing for healthcare, focusing on co‐designing computing, sensing, and energy strategies to overcome integration and power challenges for optimized, decentralized operation. ABSTRACT Recent advances in bio‐integrated healthcare technologies have enabled continuous, high‐resolution monitoring and ...
Gyuwon Kim +4 more
wiley +1 more source
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
openaire +4 more sources
3D Object Recognition with Convolutional Neural Network [PDF]
, 2016 In this work, we propose the implementation of a 3D object recognition system using Convolutional Neural Networks. For that purpose, we first analyzed the theoretical foundations of that kind of neural networks. Next, we discussed ways of representing 3D
Garcia-Garcia, Alberto
core
Advanced Materials Technologies, EarlyView.Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim +6 more
wiley +1 more source
Double Residual Network Recognition Method for Falling Abnormal Behavior
Jisuanji kexue yu tansuo, 2020 In the abnormal behavior monitoring, due to the complicated situation such as monitoring angles of view, human body postures and scenes, it is easy to cause vanishing gradient and over-fitting by directly adding 3D con-volutional neural network layers to
WANG Xinwen, XIE Linbo, PENG Li
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Feature Visualization in 3D Convolutional Neural Networks
Understanding the computations of convolutional neural networks requires effective visualization of their kernels. While maximal activation methods have proven successful in highlighting the preferred features of 2D convolutional kernels, directly applying these techniques to 3D convolutions often leads to uninterpretable results due to the higher ...
Chunpeng Li, Ya-tang Li
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Architecture of Convolutional Neural Network (CNN).
, 2023 Architecture of Convolutional Neural Network (CNN).
Anjana Makoonlall (15187823) +3 more
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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