Content-Based Feature Extraction and Extreme Learning Machine for Optimizing File Cluster Types Identification
Recent research in digital forensic attempts to classify image clusters into JPEG or non-JPEG clusters before recovering JPEG image files. This issue might improve the recovering JPEG image accuracy and reduce the processing time. In this work, three content-based feature extraction methods are used...
Saved in:
Main Authors: | Ali R.R., Al-Dayyeni W.S., Gunasekaran S.S., Mostafa S.A., Abdulkader A.H., Rachmawanto E.H. |
---|---|
Other Authors: | 57200536163 |
Format: | Conference Paper |
Published: |
Springer Science and Business Media Deutschland GmbH
2023
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Extreme learning machine classification of file clusters for evaluating content-based feature vectors
by: Ali, Rabei Raad, et al.
Published: (2018) -
Classification of JPEG files by using extreme learning machine
by: Ali, Rabei Raad, et al.
Published: (2018) -
Incorporating the Markov Chain Model in WBSN for Improving Patients� Remote Monitoring Systems
by: Ali R.R., et al.
Published: (2023) -
The Contextual Mapping of Smart City Characteristics with their Dimensions through Content Analysis Method
by: Vasudavan, H., et al.
Published: (2020) -
The Contextual Mapping of Smart City Characteristics with their Dimensions through Content Analysis Method
by: Vasudavan H., et al.
Published: (2023)