A Convolutional Neural Network for Soft Robot Images Classification

被引：0

作者：

Oguntosin, Victoria ^{[1
]}

Akindele, Ayoola ^{[1
]}

Uyi, Aiyudubie ^{[1
]}

机构：

[1] Covenant Univ, Dept Elect & Informat Engn, Ota, Ogun State, Nigeria

来源：

2020 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2020) | 2020年

关键词：

CNN classifier; convolutional neural network; soft actuators; bending actuators; triangle actuators; muscle actuators;

D O I：

10.1109/iscmi51676.2020.9311562

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, a Convolutional Neural Network (CNN) is used to classify the images of soft robotic actuators as bending, triangle, and muscle actuators. The classifier model is built with a total 390 images of soft actuators comprising the soft actuators with 130 images for bending, triangle, and muscle actuators, respectively. 70% of the images were used for training, while 30% were used for validation. The developed CNN model achieved a loss of 7.63% and accuracy of 97.6% for the training data while a loss of 9.64% and accuracy of 85.71% was obtained on the validation data.

引用

页码：110 / 114

页数：5

共 50 条

[1] On Application of Convolutional Neural Network for Classification of Plant Images
Mokeev, Vladimir V.
2018 GLOBAL SMART INDUSTRY CONFERENCE (GLOSIC), 2018,
[2] Convolutional Neural Network with SVM for Classification of Animal Images
Manohar, N.
Kumar, Y. H. Sharath
Rani, Radhika
Kumar, G. Hemantha
EMERGING RESEARCH IN ELECTRONICS, COMPUTER SCIENCE AND TECHNOLOGY, ICERECT 2018, 2019, 545 : 527 - 537
[3] Classification of retinal images based on convolutional neural network
El-Hag, Noha A.
Sedik, Ahmed
El-Shafai, Walid
El-Hoseny, Heba M.
Khalaf, Ashraf A. M.
El-Fishawy, Adel S.
Al-Nuaimy, Waleed
Abd El-Samie, Fathi E.
El-Banby, Ghada M.
MICROSCOPY RESEARCH AND TECHNIQUE, 2021, 84 (03) : 394 - 414
[4] Classification of Histopathological Images Using Convolutional Neural Network
Hatipoglu, Nuh
Bilgin, Gokhan
2014 4TH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA), 2014, : 295 - 300
[5] Convolutional Neural Network (CNN) for Gland Images Classification
Haryanto, Toto
Wasito, Ito
Suhartanto, Heru
PROCEEDINGS OF 2017 11TH INTERNATIONAL CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGY AND SYSTEMS (ICTS), 2017, : 55 - 60
[6] Classification of Tank Images Using Convolutional Neural Network
Liu, Ying
Yu, Yongbin
Wang, Lin
Nyima, Tashi
Zhaxi, Nima
Huang, Hang
Deng, Quanxin
PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020), 2020, : 210 - 214
[7] Dilated and soft attention-guided convolutional neural network for breast cancer histology images classification
Zhong, Yutong
Piao, Yan
Zhang, Guohui
MICROSCOPY RESEARCH AND TECHNIQUE, 2022, 85 (04) : 1248 - 1257
[8] Collaborative classification of hyperspectral and visible images with convolutional neural network
Zhang, Mengmeng
Li, Wei
Du, Qian
JOURNAL OF APPLIED REMOTE SENSING, 2017, 11
[9] Hyperspectral Images Classification With Gabor Filtering and Convolutional Neural Network
Chen, Yushi
Zhu, Lin
Ghamisi, Pedram
Jia, Xiuping
Li, Guoyu
Tang, Liang
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 14 (12) : 2355 - 2359
[10] Deep Convolutional Neural Network based Ship Images Classification
Mishra, Narendra Kumar
Kumar, Ashok
Choudhury, Kishor
DEFENCE SCIENCE JOURNAL, 2021, 71 (02) : 200 - 208

← 1 2 3 4 5 →