scholarly journals Approaching Adversarial Example Classification with Chaos Theory

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1201
Author(s):  
Anibal Pedraza ◽  
Oscar Deniz ◽  
Gloria Bueno
Keyword(s):  
Image Processing ◽  
Lyapunov Exponents ◽  
Chaos Theory ◽  
Daily Basis ◽  
Input Image ◽  
Discriminating Power ◽  
Wide Range ◽  
Adversarial Examples ◽  
Adversarial Example ◽  
Attack And Defense

Adversarial examples are one of the most intriguing topics in modern deep learning. Imperceptible perturbations to the input can fool robust models. In relation to this problem, attack and defense methods are being developed almost on a daily basis. In parallel, efforts are being made to simply pointing out when an input image is an adversarial example. This can help prevent potential issues, as the failure cases are easily recognizable by humans. The proposal in this work is to study how chaos theory methods can help distinguish adversarial examples from regular images. Our work is based on the assumption that deep networks behave as chaotic systems, and adversarial examples are the main manifestation of it (in the sense that a slight input variation produces a totally different output). In our experiments, we show that the Lyapunov exponents (an established measure of chaoticity), which have been recently proposed for classification of adversarial examples, are not robust to image processing transformations that alter image entropy. Furthermore, we show that entropy can complement Lyapunov exponents in such a way that the discriminating power is significantly enhanced. The proposed method achieves 65% to 100% accuracy detecting adversarials with a wide range of attacks (for example: CW, PGD, Spatial, HopSkip) for the MNIST dataset, with similar results when entropy-changing image processing methods (such as Equalization, Speckle and Gaussian noise) are applied. This is also corroborated with two other datasets, Fashion-MNIST and CIFAR 19. These results indicate that classifiers can enhance their robustness against the adversarial phenomenon, being applied in a wide variety of conditions that potentially matches real world cases and also other threatening scenarios.

scholarly journals A Survey on Universal Adversarial Attack

2021 ◽  
Author(s):  
Chaoning Zhang ◽  
Philipp Benz ◽  
Chenguo Lin ◽  
Adil Karjauv ◽  
Jing Wu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Recent Progress ◽  
New Findings ◽  
Wide Range ◽  
Adversarial Examples ◽  
Adversarial Attack ◽  
Attack And Defense ◽  
Audio Video ◽  
Significant Attention

The intriguing phenomenon of adversarial examples has attracted significant attention in machine learning and what might be more surprising to the community is the existence of universal adversarial perturbations (UAPs), i.e. a single perturbation to fool the target DNN for most images. With the focus on UAP against deep classifiers, this survey summarizes the recent progress on universal adversarial attacks, discussing the challenges from both the attack and defense sides, as well as the reason for the existence of UAP. We aim to extend this work as a dynamic survey that will regularly update its content to follow new works regarding UAP or universal attack in a wide range of domains, such as image, audio, video, text, etc. Relevant updates will be discussed at: https://bit.ly/2SbQlLG. We welcome authors of future works in this field to contact us for including your new findings.

Recent Applications of High Resolution Electron Microscopy to Crystalline Arrays of Virus Particles

1978 ◽  
Vol 36 (3) ◽  
pp. 470-482 ◽  
Author(s):  
R.W. Horne
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Analytical Techniques ◽  
Staining Technique ◽  
High Resolution Electron Microscopy ◽  
Optical Diffraction ◽  
Full Potential ◽  
Virus Particles ◽  
Resolution Electron ◽  
Wide Range

The technique of surrounding virus particles with a neutralised electron dense stain was described at the Fourth International Congress on Electron Microscopy, Berlin 1958 (see Home & Brenner, 1960, p. 625). For many years the negative staining technique in one form or another, has been applied to a wide range of biological materials. However, the full potential of the method has only recently been explored following the development and applications of optical diffraction and computer image analytical techniques to electron micrographs (cf. De Hosier & Klug, 1968; Markham 1968; Crowther et al., 1970; Home & Markham, 1973; Klug & Berger, 1974; Crowther & Klug, 1975). These image processing procedures have allowed a more precise and quantitative approach to be made concerning the interpretation, measurement and reconstruction of repeating features in certain biological systems.

A Color Coded STEM/SEM Image Storage System

1981 ◽  
Vol 39 ◽  
pp. 272-273
Author(s):  
Y. Kokubo ◽  
W. H. Hardy ◽  
J. Dance ◽  
K. Jones
Keyword(s):  
Image Processing ◽  
Electron Beam ◽  
Storage System ◽  
Particle Analysis ◽  
Specific Information ◽  
X Rays ◽  
Sem Image ◽  
Backscattered Electrons ◽  
Wide Range ◽  
Scanning Electron

A color coded digital image processing is accomplished by using JEM100CX TEM SCAN and ORTEC’s LSI-11 computer based multi-channel analyzer (EEDS-II-System III) for image analysis and display. Color coding of the recorded image enables enhanced visualization of the image using mathematical techniques such as compression, gray scale expansion, gamma-processing, filtering, etc., without subjecting the sample to further electron beam irradiation once images have been stored in the memory.The powerful combination between a scanning electron microscope and computer is starting to be widely used 1) - 4) for the purpose of image processing and particle analysis. Especially, in scanning electron microscopy it is possible to get all information resulting from the interactions between the electron beam and specimen materials, by using different detectors for signals such as secondary electron, backscattered electrons, elastic scattered electrons, inelastic scattered electrons, un-scattered electrons, X-rays, etc., each of which contains specific information arising from their physical origin, study of a wide range of effects becomes possible.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

scholarly journals Image Statistics Preserving Encrypt-then-Compress Scheme Dedicated for JPEG Compression Standard

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 421
Author(s):  
Dariusz Puchala ◽  
Kamil Stokfiszewski ◽  
Mykhaylo Yatsymirskyy
Keyword(s):  
Statistical Analysis ◽  
Image Encryption ◽  
Experimental Studies ◽  
Quality Measures ◽  
Input Image ◽  
Jpeg Compression ◽  
Image Statistics ◽  
Compression Stage ◽  
Wide Range ◽  
The Impact

In this paper, the authors analyze in more details an image encryption scheme, proposed by the authors in their earlier work, which preserves input image statistics and can be used in connection with the JPEG compression standard. The image encryption process takes advantage of fast linear transforms parametrized with private keys and is carried out prior to the compression stage in a way that does not alter those statistical characteristics of the input image that are crucial from the point of view of the subsequent compression. This feature makes the encryption process transparent to the compression stage and enables the JPEG algorithm to maintain its full compression capabilities even though it operates on the encrypted image data. The main advantage of the considered approach is the fact that the JPEG algorithm can be used without any modifications as a part of the encrypt-then-compress image processing framework. The paper includes a detailed mathematical model of the examined scheme allowing for theoretical analysis of the impact of the image encryption step on the effectiveness of the compression process. The combinatorial and statistical analysis of the encryption process is also included and it allows to evaluate its cryptographic strength. In addition, the paper considers several practical use-case scenarios with different characteristics of the compression and encryption stages. The final part of the paper contains the additional results of the experimental studies regarding general effectiveness of the presented scheme. The results show that for a wide range of compression ratios the considered scheme performs comparably to the JPEG algorithm alone, that is, without the encryption stage, in terms of the quality measures of reconstructed images. Moreover, the results of statistical analysis as well as those obtained with generally approved quality measures of image cryptographic systems, prove high strength and efficiency of the scheme’s encryption stage.

scholarly journals Early Dropout Prediction in MOOCs through Supervised Learning and Hyperparameter Optimization

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1701
Author(s):  
Theodor Panagiotakopoulos ◽  
Sotiris Kotsiantis ◽  
Georgios Kostopoulos ◽  
Omiros Iatrellis ◽  
Achilles Kameas
Keyword(s):  
Online Education ◽  
Online Courses ◽  
Early Stage ◽  
Activity Patterns ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Educational Institutions ◽  
Student Dropout ◽  
Wide Range

Over recent years, massive open online courses (MOOCs) have gained increasing popularity in the field of online education. Students with different needs and learning specificities are able to attend a wide range of specialized online courses offered by universities and educational institutions. As a result, large amounts of data regarding students’ demographic characteristics, activity patterns, and learning performances are generated and stored in institutional repositories on a daily basis. Unfortunately, a key issue in MOOCs is low completion rates, which directly affect student success. Therefore, it is of utmost importance for educational institutions and faculty members to find more effective practices and reduce non-completer ratios. In this context, the main purpose of the present study is to employ a plethora of state-of-the-art supervised machine learning algorithms for predicting student dropout in a MOOC for smart city professionals at an early stage. The experimental results show that accuracy exceeds 96% based on data collected during the first week of the course, thus enabling effective intervention strategies and support actions.

The Role of Individual and Dyadic Planning in Couples’ Daily Goal Pursuits

2021 ◽  
pp. 014616722199763
Author(s):  
Ophir Katzenelenbogen ◽  
Nina Knoll ◽  
Gertraud Stadler ◽  
Eran Bar-Kalifa
Keyword(s):  
Daily Basis ◽  
Goal Achievement ◽  
Daily Diaries ◽  
Goal Progress ◽  
Wide Range ◽  
Two Samples ◽  
Individual Planning ◽  
Goal Pursuits ◽  
Complementary Strategy

Planning promotes progress toward goal achievement in a wide range of domains. To date, planning has mostly been studied as an individual process. In couples, however, the partner is likely to play an important role in planning. This study tested the effects of individual and dyadic planning on goal progress and goal-related actions. Two samples of couples ( N = 76 and N = 87) completed daily diaries over a period of 28 and 21 days. The results indicate that individual and dyadic planning fluctuate on a daily basis and support the idea that dyadic planning is predominantly used as a complementary strategy to individual planning. As expected, individual and dyadic planning were positively associated with higher levels of action control and goal progress. In Sample 2, dyadic planning was only associated with goal progress on days in which individuals felt that they were dependent upon their partners’ behaviors to achieve their goals.

An Object-Based Image Reducing Approach

2014 ◽  
Vol 1044-1045 ◽  
pp. 1049-1052 ◽  
Author(s):  
Chin Chen Chang ◽  
I Ta Lee ◽  
Tsung Ta Ke ◽  
Wen Kai Tai
Keyword(s):  
Visual Saliency ◽  
Saliency Map ◽  
Input Image ◽  
Image Size ◽  
Target Image ◽  
Feature Maps ◽  
Object Based ◽  
Wide Range

Common methods for reducing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image reducing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

A HYPERCHAOTIC SYSTEM WITH A FOUR-WING ATTRACTOR

2009 ◽  
Vol 20 (02) ◽  
pp. 323-335 ◽  
Author(s):  
GUOSI HU ◽  
BO YU
Keyword(s):  
System Dynamics ◽  
Lyapunov Exponents ◽  
Computer Simulations ◽  
Chaotic System ◽  
Bifurcation Analysis ◽  
Topological Structure ◽  
Hyperchaotic System ◽  
Wide Range ◽  
New Chaotic System

Recently, there are many methods for constructing multi-wing/multi-scroll or hyperchaotic attractors; however, it has been noticed that the attractors with both multi-wing topological structure and hyperchaotic characteristic rarely exist. A new chaotic system, obtained by making the change on coordinate to the Hu chaotic system, can generate very complex attractors with four-wing topological structure and three positive Lyapunov exponents over a wide range of parameters. The influence of parameters varying to system dynamics is analyzed, computer simulations and bifurcation analysis is also verified in this paper.

Measurement of carbonization region on leather cutting in CO2 and diode laser-based laser beam process

2021 ◽  
pp. 095440892110563
Author(s):  
S. Vasanth ◽  
T. Muthuramalingam
Keyword(s):  
Image Processing ◽  
Laser Beam ◽  
Diode Laser ◽  
Heat Affected Zone ◽  
Diode Lasers ◽  
Standard Procedure ◽  
Wide Range ◽  
Thermal Influence ◽  
Cutting Experiments ◽  
Measurement Approach

There is a quite wide range of animal leathers such as cow leather, sheep leather and buffalo leather used for leather garments and leather goods such as bags, wallets and other customized leather articles. The drawbacks of manual cutting can be eliminated by laser-based cutting. However, unwanted carbonization is happened owing to the higher thermal influence. There is no standard procedure or method available to measure the carbonization region on leather cutting. Diode lasers can process leather rapidly and efficiently. In the present work, an attempt was proposed to introduce the image processing-based measurement approach in leather cutting using CO2 laser and diode laser. The cutting experiments were performed on sheep leather with a thickness of 1 mm. It was found that the proposed can effectively measure the heat-affected zone (HAZ) of leather cutting. It has also been found that diode laser could produce lower HAZ than CO2 laser on leather cutting.

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