A Convolutional Neural Networks Oriented Approach for Voxel-Based 3D Object Classification

被引：0

作者：

Sirma, Ridvan ^{[1
]}

Dinar, Berkan ^{[1
]}

Sahin, Yusuf Huseyin ^{[1
]}

Unal, Gozde ^{[1
]}

机构：

[1] Istanbul Tech Univ, Bilgisayar & Bilisim Fak, Istanbul, Turkey

来源：

2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2018年

关键词：

convolutional neural networks; deep learning; 3D object classification;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In our work, 3D objects classification has been dealt with convolutional neural networks which is a common paradigm recently in image recognition. In the first phase of experiments, 3D models in ModelNet10 and ModelNet40 data sets were voxelized and scaled with certain parameters. Classical CNN and 3D Dense CNN architectures were designed for training the pre-processed data. In addition, the two trained CNNs were ensembled and the results of them were observed. A success rate of 95.37% achieved on ModelNet10 by using 3D dense CNN, a success rate of 91.24% achieved with ensemble of two CNNs on ModelNet40.

引用

页数：4

共 50 条

[41] Point Cloud Object Recognition using 3D Convolutional Neural Networks
Soares, Marcelo Borghetti
Wermter, Stefan
[J]. 2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2018,
[42] Voxel-based diktiometry: Combining convolutional neural networks with voxel-based analysis and its application in diffusion tensor imaging for Parkinson's disease
Estudillo-Romero, Alfonso
Haegelen, Claire
Jannin, Pierre
Baxter, John S. H.
[J]. HUMAN BRAIN MAPPING, 2022, 43 (16) : 4835 - 4851
[43] Fused Deep Convolutional Neural Networks Based on Voting Approach for Efficient Object Classification
Ali, Redha
Ragb, Hussin K.
[J]. PROCEEDINGS OF THE 2019 IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON), 2019, : 335 - 339
[44] Brain MRI-based 3D Convolutional Neural Networks for Classification of Schizophrenia and Controls
Hu, Mengjiao
Sim, Kang
Zhou, Juan Helen
Jiang, Xudong
Guan, Cuntai
[J]. 42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 1742 - 1745
[45] Hyperspectral image classification based on optimized convolutional neural networks with 3D stacked blocks
Xiaoxia Zhang
Yong Guo
Xia Zhang
[J]. Earth Science Informatics, 2022, 15 : 383 - 395
[46] 3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts
Merino, Ibon
Azpiazu, Jon
Remazeilles, Anthony
Sierra, Basilio
[J]. SENSORS, 2021, 21 (04) : 1 - 18
[47] Hyperspectral image classification based on optimized convolutional neural networks with 3D stacked blocks
Zhang, Xiaoxia
Guo, Yong
Zhang, Xia
[J]. EARTH SCIENCE INFORMATICS, 2022, 15 (01) : 383 - 395
[48] Ensemble of PANORAMA-based convolutional neural networks for 3D model classification and retrieval
Sfikas, Konstantinos
Pratikakis, Ioannis
Theoharis, Theoharis
[J]. COMPUTERS & GRAPHICS-UK, 2018, 71 : 208 - 218
[49] Classification of Pancreatic Tumors based on MRI Images using 3D Convolutional Neural Networks
Chen, Xuan
Chen, Yufei
Ma, Chao
Liu, Xianhui
Tang, Xin
[J]. ISICDM 2018: PROCEEDINGS OF THE 2ND INTERNATIONAL SYMPOSIUM ON IMAGE COMPUTING AND DIGITAL MEDICINE, 2018, : 92 - 96
[50] 3D convolutional neural networks based automatic modulation classification in the presence of channel noise
Khan, Rahim
Yang, Qiang
Ullah, Inam
Rehman, Ateeq Ur
Bin Tufail, Ahsan
Noor, Alam
Rehman, Abdul
Cengiz, Korhan
[J]. IET COMMUNICATIONS, 2022, 16 (05) : 497 - 509

← 1 2 3 4 5 →