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Analyzing and Mitigating JPEG Compression Defects in Deep Learning [article]

Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava
2021 arXiv   pre-print
With the proliferation of deep learning methods, many computer vision problems which were considered academic are now viable in the consumer setting.  ...  Here we present a unified study of the effects of JPEG compression on a range of common tasks and datasets.  ...  Acknowledgement This project was partially supported by independent grants from Facebook AI, DARPA SemaFor (HR001119S0085) and DARPA SAIL-ON (W911NF2020009) programs.  ... 
arXiv:2011.08932v2 fatcat:zedts7ok7rcejfgmpxwrk5c4wa

Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization [article]

Myung-Joon Kwon, Seung-Hun Nam, In-Jae Yu, Heung-Kyu Lee, Changick Kim
2021 arXiv   pre-print
We focus on JPEG compression artifacts left during image acquisition and editing.  ...  It significantly outperforms traditional and deep neural network-based methods in detecting and localizing tampered regions.  ...  Table 1 1 Summary of image manipulation detection and localization methods. Top: methods not using deep learning, bottom: methods using deep learning.  ... 
arXiv:2108.12947v1 fatcat:cscerhw2rreubob7tvos7jgvhq

A Survey of Machine Learning Techniques in Adversarial Image Forensics [article]

Ehsan Nowroozi, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo
2020 arXiv   pre-print
Increasingly, machine learning approaches are also utilized in image forensics.  ...  Image forensic plays a crucial role in both criminal investigations (e.g., dissemination of fake images to spread racial hate or false narratives about specific ethnicity groups) and civil litigation (  ...  Acknowledgements The first author thanks members of the Visual Information Processing and Protection (VIPP) group at the University of Siena, Italy for their suggestions.  ... 
arXiv:2010.09680v1 fatcat:qzvolq6kvrggfbyg23wrcnykza

A survey of machine learning techniques in adversarial image forensics

Ehsan Nowroozi, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo
2020 Zenodo  
Increasingly, machine learning approaches are also utilized in image forensics.  ...  However, there are also a number of limitations and vulnerabilities associated with machine learning-based approaches (e.g., how to detect adversarial (image) examples), and there are associated real-world  ...  All authors thank the handling editor and the anonymous reviewers for their insightful critiques which help to improve the quality of this paper.  ... 
doi:10.5281/zenodo.4560205 fatcat:zuplnvtwhzhbnajteyunddphkq

Channel-Wise Spatiotemporal Aggregation Technology for Face Video Forensics

Yujiang Lu, Yaju Liu, Jianwei Fei, Zhihua Xia, Guoying Zhao
2021 Security and Communication Networks  
Recent progress in deep learning, in particular the generative models, makes it easier to synthesize sophisticated forged faces in videos, leading to severe threats on social media about personal privacy  ...  and reputation.  ...  Similarly, the study in [7] discovered the influence of times of JPEG compression that images go through.  ... 
doi:10.1155/2021/5524930 fatcat:746256j3ybfrzgvgvo3hbranjy

Modeling Lost Information in Lossy Image Compression [article]

Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu
2020 arXiv   pre-print
Most recently proposed deep-learning-based image compression methods leverage the auto-encoder structure, and reach a series of promising results in this field.  ...  In this work, we propose a novel invertible framework called Invertible Lossy Compression (ILC) to largely mitigate the information loss problem.  ...  In recent years, more and more deep-learning-based works came into sight and attained astonishing results [4] - [9] , [11] , [20] .  ... 
arXiv:2006.11999v3 fatcat:rf5iigolivasnmype36laqgdsm

Schedule

2021 2021 6th International Conference for Convergence in Technology (I2CT)  
Swati Babasaheb Bhonde Deep Learning Techniques in Cancer Prediction Using Genomic Profiles: A Systematic Review 6.00 PM 6.15 PM 10 817 Sneha Madane Social Distancing Detection and Analysis  ...  Sadik Hossain 10.301 AM 10.45 AM 9 770 PRAJNA KOTIAN Detection of Malware in Cloud Environment using Deep Neural Network 10.45 AM 11.00 AM 10 824 Swati Bhonde Deep Learning Techniques  ... 
doi:10.1109/i2ct51068.2021.9417932 fatcat:werfkg6g65dfzesamouckqcxhy

London Imaging Meeting 2021: Imaging for Deep Learning

2021 London Imaging Meeting  
Accordingly, an increasing number of conventional and deep learning reconstruction approaches have been introduced in recent years.  ...  Preliminary results indicate that re-training the neural network with M-JPEG compressed 15:00 London / 10:00 NY / 22:00 Beijing Revisiting and Optimising a CNN Colour Constancy Method for Multi- illuminant  ... 
doi:10.2352/issn.2694-118x.2021.lim-a fatcat:fcp5nppy2rcibfaj3yllh7oe54

Overview and Empirical Analysis of ISP Parameter Tuning for Visual Perception in Autonomous Driving

Lucie Yahiaoui, Jonathan Horgan, Brian Deegan, Senthil Yogamani, Ciarán Hughes, Patrick Denny
2019 Journal of Imaging  
The rise in prominence of autonomous driving and computer vision brings to the fore research in the area of the impact of image quality in camera perception for tasks such as recognition, localization  ...  and reconstruction.  ...  For example in the paper [84] , the authors observed a reduction of performance of different Deep Neural Network architectures under blur and noise, while being resilient to contrast and JPEG compression  ... 
doi:10.3390/jimaging5100078 pmid:34460644 pmcid:PMC8321211 fatcat:xfjotfq72za6vev6epmmtycvxy

Automated Classification of Helium Ingress in Irradiated X-750 [article]

Chris Anderson, Jacob Klein, Heygaan Rajakumar, Colin Judge, Laurent K Beland
2020 arXiv   pre-print
Analyzing these micrographs is often a tedious and labour intensive manual process. It is a prime candidate for automation.  ...  Imaging nanoscale features using transmission electron microscopy is key to predicting and assessing the mechanical behavior of structural materials in nuclear reactors.  ...  Deep learning shows promise, and can likely be used to improve many other aspects of characterization of materials, including those used for nuclear power generation. VI.  ... 
arXiv:1912.04252v2 fatcat:z3ocgmxirrdyzesor7ntuzach4

Adversarial Attacks and Defenses in Deep Learning: from a Perspective of Cybersecurity

Shuai Zhou, Chi Liu, Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu
2022 ACM Computing Surveys  
Many papers have been published on adversarial attacks and their countermeasures in the realm of deep learning.  ...  The outstanding performance of deep neural networks has promoted deep learning applications in a broad set of domains.  ...  To mitigate the safety and privacy concerns in deep learning and promote "deep learning as-a-service", there must be more studies on model security.  ... 
doi:10.1145/3547330 fatcat:d3x3oitysvb73ado5kuaqakgtu

Improving robustness against common corruptions by covariate shift adaptation [article]

Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge
2020 arXiv   pre-print
Today's state-of-the-art machine vision models are vulnerable to image corruptions like blurring or compression artefacts, limiting their performance in many real-world applications.  ...  The key insight is that in many scenarios, multiple unlabeled examples of the corruptions are available and can be used for unsupervised online adaptation.  ...  Acknowledgments and Disclosure of Funding  ... 
arXiv:2006.16971v2 fatcat:xwtrxkhidnc2dmg75cppkfxgp4

DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment [article]

Bing Yu and Hua Qi and Qing Guo and Felix Juefei-Xu and Xiaofei Xie and Lei Ma and Jianjun Zhao
2020 arXiv   pre-print
We propose a style transfer method to learn and introduce the unknown failure patterns within the failure data into the training data via data augmentation.  ...  and the potential unknown noise factors in the operational environment, e.g., weather, blur, noise etc.  ...  JPEG compression.  ... 
arXiv:2011.09884v1 fatcat:orurpxhbzzhzpg5mqrymo7fwli

National Conference on Recent Advances in Communication Engineering and Information Technology

2020 International journal for innovative engineering and management research  
We provide a broad-based engineering curriculum, with opportunities for specialization and self-directed learning and development.  ...  We invest much effort to enhance our student's learning experience through the application of ECE technology.  ...  and respective contrast parameter is analyzed for the defect detection.  ... 
doi:10.48047/ijiemr/v08/spe/02 fatcat:woay334irjgebf5bixuc4ng6em

Survey on Botnet Detection Techniques: Classification, Methods, and Evaluation

Ying Xing, Hui Shu, Hao Zhao, Dannong Li, Li Guo, Jude Hemanth
2021 Mathematical Problems in Engineering  
This survey analyzes and compares the most important efforts in the botnet detection area in recent years.  ...  It focuses on the application of advanced technologies such as deep learning, complex network, swarm intelligence, moving target defense (MTD), and software-defined network (SDN) for botnet detection.  ...  Acknowledgments is paper was supported by the National Key Research and Development Project (2016YFB08011601). e authors would like to acknowledge the support.  ... 
doi:10.1155/2021/6640499 fatcat:hkafnnj2cnbzjdbuk6iel3b5cm
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