Learned Perceptual Image Enhancement

Learning a typical image enhancement pipeline involves minimization of a loss function between enhanced and reference images. While L1 and L2 losses are perhaps the most widely used functions for this purpose, they do not necessarily lead to perceptually compelling results. In this paper, we show that adding a learned no-reference image quality metric to the loss can significantly improve enhancement operators. This metric is implemented using a CNN (convolutional neural network) trained on a large-scale dataset labelled with aesthetic preferences of human raters. This loss allows us to conveniently perform back-propagation in our learning framework to simultaneously optimize for similarity to a given ground truth reference and perceptual quality. This perceptual loss is only used to train parameters of image processing operators, and does not impose any extra complexity at inference time. Our experiments demonstrate that this loss can be effective for tuning a variety of operators such as local tone mapping and dehazing

Finite Element Modeling Of Ballistic Penetration into Fabric Armor

The goal of this work is to analyze the ballistic performance of plain woven fabric used in soft armor systems using a detailed finite element analysis at yarn level. As more complex materials systems are introduced in engineering practice, the design engineer faces the dilemma of utilizing homogenization techniques or detailed numerical models. The latter offers a number of advantages, such as the ability to introduce separate constitutive laws and failure criteria for each phase, at the expense of computation cost. This is particularly important in ballistic performance of the soft armor where the projectile-fabric interaction and failure modes are complicated and can not be realized in other approaches. An automatic geometry generation algorithm for textile is developed that can generate complex fabric geometries spanning several unit cells. This program (named DYNTEX) based on the mentioned algorithm is designed using MATLAB code. A commercial finite element code named LS-DYNA is used as the solver and DYNTEX program is then extended to do the pre-processing for LS-DYNA. Four types of projectile shapes were chosen which consist of spherical, blunt, conical, hemi-spherical and a conically cylindrical military sized bullet. An orthotropic material with von-Mises stress at failure of 2.7GPa was chosen for material behavior of yarns. Since projectiles did not have considerable deformation, they assumed as rigid bodies. Furthermore a general surface to surface contact was selected for the contact between the yarns and projectile-fabric. Initial conditions and results of experimentations were extracted from literature to validate the simulation results for different projectile shapes. To verify the mesh built by DYNTEX program a relatively low velocity impact simulation performed in oblique angle. Then convergence analysis is then carried out by changing the mesh density of fabric target and it was shown primary mesh density was fine enough to start the remaining simulations. Finite element models of fabric impact were made with initial conditions extracted from literature and simulations were performed. The results of simulations showed close agreement with experimental tests. Moreover several parameters which affect the energy absorption of fabric were studied. These parameters were friction, boundary conditions, projectile nose diameter and projectile nose angle. The mentioned parameters were studied with respect to several projectile nose shapes and boundary conditions

Interval-valued intuitionistic fuzzy soft graph

One of the theories designed to deal with uncertainty is the soft set theory. These collections were used due to a lack of membership functions in the fields of decision-making, systems analysis, classification, data mining, medical diagnosis, etc. Fuzzy graphs based on soft sets were developed alongside fuzzy graphs. Studying these graphs, examining the properties and operators on it, give special flexibility in dealing with indeterminate problems. In particular, most of the issues around us are mixed and operations are conveniently used in many combinatorial applications. Therefore, the study of operations have a significant effect on solving problems based on decisionmaking, medical, etc. In this paper, we introduce the notion of interval-valued intuitionistic fuzzy soft graphs, by combine concepts of interval-valued intuitionistic fuzzy graphs and fuzzy soft graphs. We also present several different types of operations including cartesian product, strong product and composition on interval-valued intuitionistic fuzzy soft graphs and investigate some properties of them.Publisher's Versio

Some properties of vague graph structures

A graph structure is a generalization of simple graphs. Graph structures are very useful tools for the study of different domains of computational intelligence and computer science. A vague graph structure is a generalization of a vague graph. In this research paper, we present several different types of operations including cartesian product, cross product, lexicographic product, union, and composition on vague graph structures. We also introduce some results of operations.Publisher's Versio

Extraction of Nucleolus Candidate Zone in White Blood Cells of Peripheral Blood Smear Images Using Curvelet Transform

The main part of each white blood cell (WBC) is its nucleus which contains chromosomes. Although white blood cells (WBCs) with giant nuclei are the main symptom of leukemia, they are not sufficient to prove this disease and other symptoms must be investigated. For example another important symptom of leukemia is the existence of nucleolus in nucleus. The nucleus contains chromatin and a structure called the nucleolus. Chromatin is DNA in its active form while nucleolus is composed of protein and RNA, which are usually inactive. In this paper, to diagnose this symptom and in order to discriminate between nucleoli and chromatins, we employ curvelet transform, which is a multiresolution transform for detecting 2D singularities in images. For this reason, at first nuclei are extracted by means of K-means method, then curvelet transform is applied on extracted nuclei and the coefficients are modified, and finally reconstructed image is used to extract the candidate locations of chromatins and nucleoli. This method is applied on 100 microscopic images and succeeds with specificity of 80.2% and sensitivity of 84.3% to detect the nucleolus candidate zone. After nucleolus candidate zone detection, new features that can be used to classify atypical and blast cells such as gradient of saturation channel are extracted

The first integral method and traveling wave solutions to Davey–Stewartson equation

In this paper, the first integral method will be applied to integrate the Davey–Stewartson’s equation. Using this method, a few exact solutions will be obtained using ideas from the theory of commutative algebra. Finally, soliton solution will also be obtained using the traveling wave hypothesis