Optimal dense convolutional network model for image classification in unmanned aerial vehicles based ad hoc networks

Punithavathi I. S. Hephzi; Dhanasekaran S.; Duraipandy P.Lydia E. LaxmiSivaram M.Shankar K.

首页> 外文期刊>International journal of ad hoc and ubiquitous computing: IJAHUC >Optimal dense convolutional network model for image classification in unmanned aerial vehicles based ad hoc networks

【24h】

Optimal dense convolutional network model for image classification in unmanned aerial vehicles based ad hoc networks

机译：Optimal dense convolutional network model for image classification in unmanned aerial vehicles based ad hoc networks

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相关主题

摘要

Unmanned aerial vehicles (UAVs) have the potential of generating an ad hoc communication network on the fly. Aerial image classification gains more importance in the remote sensing community and several studies have been carried out in recent days. This paper presents an optimal dense convolutional network (DenseNet) with bidirectional long short term memory (Bi-LSTM) based image classification model called optimal DenseNet (ODN)-BiLSTM for UAV based adhoc networks. DenseNet model is applied as a feature extractor, where the hyperparameters of DenseNet are tuned by the use of Adagrad optimiser. Secondly, the Bi-LSTM model is applied as a classifier, which classifies the aerial images captured by UAV. Detailed performance analysis of the proposed model takes place using UCM aerial dataset and the results are investigated under several dimensions. The ODN-BiLSTM model has provided effective image classification results with the maximum accuracy of 98.14% and minimum execution time of 80s.

著录项

来源
《International journal of ad hoc and ubiquitous computing: IJAHUC》 |2022年第2期|46-57|共12页
作者
Punithavathi I. S. Hephzi; Dhanasekaran S.; Duraipandy P.Lydia E. LaxmiSivaram M.Shankar K.;
展开▼
作者单位

Sphoorthy Engn Coll, Dept Comp Sci & Engn, Hyderabad, India;

Kalasalingam Univ, Dept Comp Sci & Engn, Srivilliputtur, India;

JB Inst Engn & Technol, Dept Elect & Elect Engn, Hyderabad, IndiaVignans Inst Informat Technol Autonomous, Comp Sci & Engn, Visakhapatnam, Andhra Pradesh, IndiaLebanese French Univ, Dept Comp Networking, Erbil, Kurdistan Regio, IraqAlagappa Univ, Dept Comp Applicat, Karaikkudi, Tamil Nadu, India;

展开▼
收录信息
原文格式 PDF
正文语种英语
中图分类
关键词
ad hoc networks; deep learning; image classification; unmanned aerial vehicle; UAV;

Optimal dense convolutional network model for image classification in unmanned aerial vehicles based ad hoc networks

摘要

著录项

相关主题

期刊订阅