1. Shodhganga@INFLIBNET
  2. Jaypee Institute of Information Technology
  3. Department of Electronics and Communication Engineering
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/549123
Title: Machine learning based passive image forgery classification using Hybrid- Handcrafted and CNN based features
Researcher: Agarwal, Aanchal
Guide(s): Khandelwal, Vineet
Keywords: 2D-DCT, filtered residual.
3D-CNN, double
Electronics and Communication Engineering
Engineering
Engineering and Technology
Engineering Multidisciplinary
general purpose detectors,
JPEG detection,
Passive image forensics,
University: Jaypee Institute of Information Technology
Completed Date: 2024
Abstract: included newline
URI: http://hdl.handle.net/10603/549123
Appears in Departments:Department of Electronics and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File298.32 kBAdobe PDFView/Open
02_prelim pages.pdf850.81 kBAdobe PDFView/Open
03_table of contents.pdf216.69 kBAdobe PDFView/Open
04_abstract.pdf204.21 kBAdobe PDFView/Open
05_chapter1.pdf2.54 MBAdobe PDFView/Open
06_chapter2.pdf1.2 MBAdobe PDFView/Open
07_chapter3.pdf1.54 MBAdobe PDFView/Open
08_chapter4.pdf841.65 kBAdobe PDFView/Open
09_chapter5.pdf1.26 MBAdobe PDFView/Open
10_chapter6.pdf4.85 MBAdobe PDFView/Open
11_references.pdf1.09 MBAdobe PDFView/Open
12_list of publications.pdf258.93 kBAdobe PDFView/Open
13_synopsis.pdf1.25 MBAdobe PDFView/Open
80_recommendation.pdf391.98 kBAdobe PDFView/Open
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