Results 1 to 10 of about 6,781,577 (302)

CT images-based 3D convolutional neural network to predict early recurrence of solitary hepatocellular carcinoma after radical hepatectomy [PDF]

Diagnostic and Interventional Radiology, 2022
PURPOSEThe high rate of recurrence of hepatocellular carcinoma (HCC) after radical hepatectomy is an important factor that affects the long-term survival of patients.
Hao Cui, Kun-Yuan Wang, Wen-Yuan Li, Hong-Bo Zhu, Lu-Shan Xiao, Li Liu   +5 more
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Classification of 3D CAD Models considering the Knowledge Recognition Algorithm of Convolutional Neural Network

Advances in Multimedia, 2022
In order to improve the classification effect of the 3D CAD model, this paper combines the knowledge recognition algorithm of convolutional neural network to construct the 3D CAD model classification model.
Weiwei Wang, Dandan Sun
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DIAGNOSIS OF ALZHEIMER'S DISEASE BY THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK USING UNSUPERVISED FEATURE LEARNING METHOD [PDF]

International Journal of Intelligent Computing and Information Sciences, 2022
The rise of Deep Learning in the past two decades has prompted research into solutions to help improve Alzheimer’s diagnosis based on neuroimaging data.
Abdel-Badeeh M. Salem, El-Sayed A. El-Dahshan, Sarah A. Soliman   +2 more
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Polarimetric SAR image classification using 3D generative adversarial network [PDF]

MATEC Web of Conferences, 2021
In this paper, a new architecture of three-dimensional deep convolutional generative adversarial network(3D-DCGAN) is specially defined to solve the unstable training problem of GAN and make full use of the information involved in polarimetric data ...
Liu Lu, Feng Guobao
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MixFormer: A Self-Attentive Convolutional Network for 3D Mesh Object Recognition

Algorithms, 2023
3D mesh as a complex data structure can provide effective shape representation for 3D objects, but due to the irregularity and disorder of the mesh data, it is difficult for convolutional neural networks to be directly applied to 3D mesh data processing.
Lingfeng Huang, Jieyu Zhao, Yu Chen
doaj   +1 more source

2DSlicesNet: A 2D Slice-Based Convolutional Neural Network for 3D Object Retrieval and Classification

IEEE Access, 2021
3D data can be instrumental to the computer vision field as it provides insightful information about the full 3D models' geometry. Recently, with easy access to both computational power and huge 3D databases, it is feasible to apply convolutional neural ...
Ilyass Ouazzani Taybi, Taoufiq Gadi, Rachid Alaoui   +2 more
doaj   +1 more source

A 3D Fluorescence Classification and Component Prediction Method Based on VGG Convolutional Neural Network and PARAFAC Analysis Method

Applied Sciences, 2022
Three-dimensional fluorescence is currently studied by methods such as parallel factor analysis (PARAFAC), fluorescence regional integration (FRI), and principal component analysis (PCA).
Kun Ruan, Shun Zhao, Xueqin Jiang, Yixuan Li, Jianbo Fei, Dinghua Ou, Qiang Tang, Zhiwei Lu, Tao Liu, Jianguo Xia   +9 more
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Mobile robot 3D trajectory estimation on a multilevel surface with multimodal fusion of 2D camera features and a 3D light detection and ranging point cloud

International Journal of Advanced Robotic Systems, 2022
Nowadays, multi-sensor fusion is a popular tool for feature recognition and object detection. Integrating various sensors allows us to obtain reliable information about the environment.
Vinicio Rosas-Cervantes, Quoc-Dong Hoang, Sooho Woo, Soon-Geul Lee   +3 more
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Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles

Frontiers in Neuroinformatics, 2022
ObjectiveTo explore the feasibility of a deep learning three-dimensional (3D) V-Net convolutional neural network to construct high-resolution computed tomography (HRCT)-based auditory ossicle structure recognition and segmentation models.MethodsThe ...
Xing-Rui Wang, Xi Ma, Liu-Xu Jin, Yan-Jun Gao, Yong-Jie Xue, Jing-Long Li, Wei-Xian Bai, Miao-Fei Han, Qing Zhou, Feng Shi, Jing Wang   +10 more
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Hybrid Convolutional Network Combining Multiscale 3D Depthwise Separable Convolution and CBAM Residual Dilated Convolution for Hyperspectral Image Classification

Remote Sensing, 2023
In recent years, convolutional neural networks (CNNs) have been increasingly leveraged for the classification of hyperspectral imagery, displaying notable advancements. To address the issues of insufficient spectral and spatial information extraction and
Yicheng Hu, Shufang Tian, Jia Ge
doaj   +1 more source