dc.contributor.author |
R, Vasudeva. |
|
dc.contributor.author |
S.N, Dr Chandrashekara |
|
dc.date.accessioned |
2022-12-06T19:47:31Z |
|
dc.date.available |
2022-12-06T19:47:31Z |
|
dc.date.issued |
2022-12-06 |
|
dc.identifier.issn |
2210-142X |
|
dc.identifier.uri |
https://journal.uob.edu.bh:443/handle/123456789/4697 |
|
dc.description.abstract |
The world is full of digital data disseminated everywhere for creating, accessing, and storing information among the people’s
communication through media with network devices. The huge volume of data stored as a repository in a remote place where it
is accessed in terms of datasets/databases. Such kinds of databases are extracted from the repositories in a short period based on
its features and contents available inside the databases. The processing of transformation of data from one form to another using
the above-said functions of a database plays a vital role in extracting information on large networks. Information Retrieval (IR) is
the normal technique to derive the information from the warehouses through its features and functionalities. Cloud computing is
the trending technique to store the accessed information and converted it into meaningful data as a database and stored in a remote
place among the nodes of networks. The stored databases are collected and combined as a group of data based on the features
present in the database then stored as clusters. Separate clusters are created in the cloud to store text, audio, video, and multimedia
supported files remotely from different sources on the internet. From those clusters, extracting the accurate files needed should be
processed through various classical algorithms and techniques with the supported tools. Content-Based Image Retrieval (CBIR) is the
common popular technique used to get accurate results as an output from the cloud clusters in a short duration of time. The latency
and efficiency will be very low to process the huge volume of data on the network. Classical approaches implemented innovative
ideas such as query-based approach, features extraction, auto-encoders, and indexing on this CBIR technique and applied them
through machine learning algorithms, CNN (Convolution Neural Networks), and deep learning. Since cloud computing is working
with the internet as an important phenomenon all the techniques are needed for internet sources. The accuracy and latency of the
CBIR technique on cloud storage servers is a challenging mission for people who are needed in different sectors, especially in
healthcare. To find better solutions for the above-said problem this survey paper has been written from a technical perspective view, and
helpful to the researchers get motivated to do their innovative works, and ideas on the CBIR model to emphasize in the competitive world. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
University of Bahrain |
en_US |
dc.subject |
Information Retrieval, Cloud Computing, Content Based Image Retrieval, Machine Learning, Convolution Neural Networks. |
en_US |
dc.title |
A Comprehensive Study on Image Retrieval Algorithms of Cloud Storage for Information Extraction in Health Care System |
en_US |
dc.type |
Article |
en_US |
dc.identifier.doi |
https://dx.doi.org/10.12785/ijcds/1201106 |
|
dc.volume |
12 |
en_US |
dc.issue |
1 |
en_US |
dc.pagestart |
1315 |
en_US |
dc.pageend |
1328 |
en_US |
dc.contributor.authoraffiliation |
Department of Computer Science and Engineering, C Byregowda Institute of Technology, Kolar, Karnataka, India |
en_US |
dc.source.title |
International Journal of Computing and Digital Systems |
en_US |
dc.abbreviatedsourcetitle |
IJCDS |
en_US |