Nitin Khanna, Ph.D.
Affiliations: | 2009 | Electrical and Computer Engineering | Purdue University, West Lafayette, IN, United States |
Area:
Electronics and Electrical Engineering, Computer ScienceGoogle:
"Nitin Khanna"Parents
Sign in to add mentor| Edward J. Delp | grad student | 2009 | Purdue | |
| (Forensic characterization of image capture devices.) | ||||
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Publications
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| Joshi S, Khanna N. (2020) Source Printer Classification Using Printer Specific Local Texture Descriptor Ieee Transactions On Information Forensics and Security. 15: 160-171 |
| Jain H, Joshi S, Gupta G, et al. (2020) Passive classification of source printer using text-line-level geometric distortion signatures from scanned images of printed documents Multimedia Tools and Applications. 79: 1-24 |
| Joshi S, Saxena S, Khanna N. (2019) First steps toward CNN based source classification of document images shared over messaging app Signal Processing-Image Communication. 78: 32-41 |
| Verma V, Agarwal N, Khanna N. (2018) DCT-domain deep convolutional neural networks for multiple JPEG compression classification Signal Processing-Image Communication. 67: 22-33 |
| Joshi S, Khanna N. (2017) Single Classifier-based Passive System for Source Printer Classification using Local Texture Features Ieee Transactions On Information Forensics and Security. 13: 1603-1614 |
| Ahmad Z, Kerr DA, Bosch M, et al. (2016) A Mobile Food Record For Integrated Dietary Assessment. Madima'16 : Proceedings of the 2nd International Workshop On Multimedia Assisted Dietary Management : October 16, 2016, Amsterdam, the Netherlands. International Workshop On Multimedia Assisted Dietary Management (2nd : 2016 : Amsterdam.... 2016: 53-62 |
| Eicher-Miller HA, Khanna N, Boushey CJ, et al. (2016) Temporal Dietary Patterns Derived among the Adult Participants of the National Health and Nutrition Examination Survey 1999-2004 Are Associated with Diet Quality. Journal of the Academy of Nutrition and Dietetics. 116: 283-91 |
| Zhu F, Bosch M, Khanna N, et al. (2015) Multiple hypotheses image segmentation and classification with application to dietary assessment. Ieee Journal of Biomedical and Health Informatics. 19: 377-88 |
| He Y, Xu C, Khanna N, et al. (2014) ANALYSIS OF FOOD IMAGES: FEATURES AND CLASSIFICATION. Proceedings. International Conference On Image Processing. 2014: 2744-2748 |
| Ahmad Z, Khanna N, Kerr DA, et al. (2014) A Mobile Phone User Interface for Image-Based Dietary Assessment. Proceedings of Spie--the International Society For Optical Engineering. 9030 |