Robotic Arm Control By Fine-Tuned Convolutional Neural Network Model

被引：0

作者：

Bayraktar, Ertugrul ^{[1
]}

Yigit, Cihat Bora ^{[2
]}

Boyraz, Pinar ^{[2
]}

机构：

[1] Istanbul Tech Univ, Fen Bilimleri Enstitusu, Mekatron Muhendisligi, Istanbul, Turkey

[2] Istanbul Tech Univ, Makina Fak, Makina Muhendisligi, Istanbul, Turkey

来源：

2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2017年

关键词：

deep convolutional neural networks; object recognition; robotics; control; OBJECT;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Obtaining semantic information is crucial in order to implement complex robotic applications successfully. Therefore, it commonly expected from the robotics systems to be equipped with advanced hardware and software. In this study, the simulation results of a robotic arm, which manipulates the recognized objects using deep neural networks considering the physical features, are given for 10 different categories. An accuracy rate of %97.28 is achieved as a result of the fine-tuning of the deep neural network called VGGNet16 by using the dataset which is composed of 1000 training images and 400 testing images in each category. In addition, successful displacement results are obtained for all objects.

引用

页数：4

共 50 条

[21] A Fine-tuned deep convolutional neural network for chest radiography image classification on COVID-19 cases
Amiya Kumar Dash
Puspanjali Mohapatra
Multimedia Tools and Applications, 2022, 81 : 1055 - 1075
[22] Concrete slump prediction modeling with a fine-tuned convolutional neural network: hybridizing sea lion and dragonfly algorithms
Kumar Shaswat
Environmental Science and Pollution Research, 2022, 29 : 43758 - 43769
[23] Concrete slump prediction modeling with a fine-tuned convolutional neural network: hybridizing sea lion and dragonfly algorithms
Shaswat, Kumar
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (29) : 43758 - 43769
[24] A Fine-tuned deep convolutional neural network for chest radiography image classification on COVID-19 cases
Dash, Amiya Kumar
Mohapatra, Puspanjali
MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (01) : 1055 - 1075
[25] Online handwritten Gurmukhi word recognition using fine-tuned Deep Convolutional Neural Network on offline features
Singh, Sukhdeep
Sharma, Anuj
Chauhan, Vinod Kumar
MACHINE LEARNING WITH APPLICATIONS, 2021, 5
[26] Acquisition of Image Features for Material Perception from Fine-tuned Convolutional Neural Networks
Kobayashi, Daisuke
Yata, Noriko
Manabe, Yoshitsugu
2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 545 - 550
[27] Dermoscopic Image Classification Method Using an Ensemble of Fine-Tuned Convolutional Neural Networks
Shen, Xin
Wei, Lisheng
Tang, Shaoyu
SENSORS, 2022, 22 (11)
[28] Ensemble of fine-tuned convolutional neural networks for urine sediment microscopic image classification
Liu, Wenqian
Li, Weihong
Gong, Weiguo
IET COMPUTER VISION, 2020, 14 (01) : 18 - 25
[29] Blending Ensemble of Fine-Tuned Convolutional Neural Networks Applied to Mammary Image Classification
Zhang, Jingyi
Pan, Shuwan
Hong, Huichao
Kong, Lingke
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2019, 9 (06) : 1160 - 1166
[30] Detection and classification of breast cancer in mammographic images with fine-tuned convolutional neural networks
Luong, Huong Hoang
Nguyen, Hai Thanh
Thai-Nghe, Nguyen
JOURNAL OF INFORMATION AND TELECOMMUNICATION, 2024,

← 1 2 3 4 5 →