Search results for " Soft"

showing 10 items of 1710 documents

Perceptually Optimized Image Rendering

2017

We develop a framework for rendering photographic images by directly optimizing their perceptual similarity to the original visual scene. Specifically, over the set of all images that can be rendered on a given display, we minimize the normalized Laplacian pyramid distance (NLPD), a measure of perceptual dissimilarity that is derived from a simple model of the early stages of the human visual system. When rendering images acquired with a higher dynamic range than that of the display, we find that the optimization boosts the contrast of low-contrast features without introducing significant artifacts, yielding results of comparable visual quality to current state-of-the-art methods, but witho…

FOS: Computer and information sciencesComputer Science - Artificial IntelligenceImage qualityComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyLuminanceRendering (computer graphics)Computer Science - GraphicsOptics0202 electrical engineering electronic engineering information engineeringComputer visionPower functionComputingMethodologies_COMPUTERGRAPHICSbusiness.industryDynamic range020207 software engineeringAtomic and Molecular Physics and OpticsGraphics (cs.GR)Electronic Optical and Magnetic MaterialsArtificial Intelligence (cs.AI)Human visual system model020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessImage compression
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Hybrid blind robust image watermarking technique based on DFT-DCT and Arnold transform

2018

In this paper, a robust blind image watermarking method is proposed for copyright protection of digital images. This hybrid method relies on combining two well-known transforms that are the discrete Fourier transform (DFT) and the discrete cosine transform (DCT). The motivation behind this combination is to enhance the imperceptibility and the robustness. The imperceptibility requirement is achieved by using magnitudes of DFT coefficients while the robustness improvement is ensured by applying DCT to the DFT coefficients magnitude. The watermark is embedded by modifying the coefficients of the middle band of the DCT using a secret key. The security of the proposed method is enhanced by appl…

FOS: Computer and information sciencesComputer Science - Cryptography and SecurityComputer Networks and CommunicationsComputer scienceMultiple Watermarking02 engineering and technologyDiscrete Fourier transformImage (mathematics)Digital imageDiscrete Fourier transform (DFT)SchemeRobustness (computer science)Quantization0202 electrical engineering electronic engineering information engineeringMedia TechnologyDiscrete cosine transformHybrid method[INFO]Computer Science [cs]Digital watermarkingDiscrete cosine transform (DCT)DistanceImage watermarking020207 software engineeringWatermarkMultimedia (cs.MM)Hardware and ArchitectureMedical ImagesEmbedding020201 artificial intelligence & image processingArnold transformWavelet DomainSvdCryptography and Security (cs.CR)AlgorithmCopyright protectionSoftwareComputer Science - Multimedia
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A Robust Blind 3-D Mesh Watermarking Technique Based on SCS Quantization and Mesh Saliency for Copyright Protection

2019

Due to the recent demand of 3-D meshes in a wide range of applications such as video games, medical imaging, film special effect making, computer-aided design (CAD), among others, the necessity of implementing 3-D mesh watermarking schemes aiming to protect copyright has increased in the last decade. Nowadays, the majority of robust 3-D watermarking approaches have mainly focused on the robustness against attacks while the imperceptibility of these techniques is still a serious challenge. In this context, a blind robust 3-D mesh watermarking method based on mesh saliency and scalar Costa scheme (SCS) for Copyright protection is proposed. The watermark is embedded by quantifying the vertex n…

FOS: Computer and information sciencesComputer Science - Cryptography and SecurityComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingQuantization (signal processing)Data_MISCELLANEOUS020207 software engineeringWatermark02 engineering and technologyGraphics (cs.GR)Computer Science - Graphics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer engineering0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPolygon meshVertex normalQuantization (image processing)Digital watermarkingCryptography and Security (cs.CR)ComputingMilieux_MISCELLANEOUSSmoothing
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Sequentializing Parameterized Programs

2012

We exhibit assertion-preserving (reachability preserving) transformations from parameterized concurrent shared-memory programs, under a k-round scheduling of processes, to sequential programs. The salient feature of the sequential program is that it tracks the local variables of only one thread at any point, and uses only O(k) copies of shared variables (it does not use extra counters, not even one counter to keep track of the number of threads). Sequentialization is achieved using the concept of a linear interface that captures the effect an unbounded block of processes have on the shared state in a k-round schedule. Our transformation utilizes linear interfaces to sequentialize the progra…

FOS: Computer and information sciencesComputer Science - Logic in Computer ScienceScheduleComputer scienceD.2.4;F.3.1Interface (computing)Parameterized complexitymodel-checking02 engineering and technologyThread (computing)computer.software_genrelcsh:QA75.5-76.95parameterized programsComputer Science - Software Engineeringsoftware verification0202 electrical engineering electronic engineering information engineeringBlock (data storage)Programming languagelcsh:MathematicsD.2.4Local variable020207 software engineeringlcsh:QA1-939Logic in Computer Science (cs.LO)Software Engineering (cs.SE)Transformation (function)model-checking; software verification; parameterized programs020201 artificial intelligence & image processinglcsh:Electronic computers. Computer scienceState (computer science)F.3.1computerElectronic Proceedings in Theoretical Computer Science
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A General Framework for Complex Network-Based Image Segmentation

2019

International audience; With the recent advances in complex networks theory, graph-based techniques for image segmentation has attracted great attention recently. In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection algorithms. If we consider regions as communities, using community detection algorithms directly can lead to an over-segmented image. To address this problem, we start by splitting the image into small regions using an initial segmentation. The obtained regions are used for building the complex network. To produce meaningful connected components and detect …

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Networks and CommunicationsComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMachine Learning (stat.ML)02 engineering and technologyMachine Learning (cs.LG)Statistics - Machine Learning0202 electrical engineering electronic engineering information engineeringMedia TechnologySegmentationConnected componentbusiness.industrySimilarity matrix[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentationComplex networkHardware and ArchitectureComputer Science::Computer Vision and Pattern RecognitionGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusinessSoftware
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Deep Non-Line-of-Sight Reconstruction

2020

The recent years have seen a surge of interest in methods for imaging beyond the direct line of sight. The most prominent techniques rely on time-resolved optical impulse responses, obtained by illuminating a diffuse wall with an ultrashort light pulse and observing multi-bounce indirect reflections with an ultrafast time-resolved imager. Reconstruction of geometry from such data, however, is a complex non-linear inverse problem that comes with substantial computational demands. In this paper, we employ convolutional feed-forward networks for solving the reconstruction problem efficiently while maintaining good reconstruction quality. Specifically, we devise a tailored autoencoder architect…

FOS: Computer and information sciencesComputer Science - Machine Learningbusiness.industryComputer scienceComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionNonlinear optics020207 software engineering02 engineering and technologyIterative reconstructionInverse problemElectrical Engineering and Systems Science - Image and Video ProcessingAutoencoderRendering (computer graphics)Machine Learning (cs.LG)Non-line-of-sight propagation0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness
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Saying Hello World with MOLA - A Solution to the TTC 2011 Instructive Case

2011

This paper describes the solution of Hello World transformations in MOLA transformation language. Transformations implementing the task are relatively straightforward and easily inferable from the task specification. The required additional steps related to model import and export are also described.

FOS: Computer and information sciencesComputer Science - Programming LanguagesbiologyComputer scienceProgramming languagelcsh:Mathematicsbiology.organism_classificationcomputer.software_genrelcsh:QA1-939Transformation languagelcsh:QA75.5-76.95Task (project management)Software Engineering (cs.SE)Computer Science - Software EngineeringMolaInstructive caselcsh:Electronic computers. Computer sciencecomputerProgramming Languages (cs.PL)Electronic Proceedings in Theoretical Computer Science
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RationalizeRoots: Software Package for the Rationalization of Square Roots

2019

The computation of Feynman integrals often involves square roots. One way to obtain a solution in terms of multiple polylogarithms is to rationalize these square roots by a suitable variable change. We present a program that can be used to find such transformations. After an introduction to the theoretical background, we explain in detail how to use the program in practice.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryHigh energy particleFeynman integralComputationGeneral Physics and AstronomyFOS: Physical sciencesengineering.materialSymbolic Computation (cs.SC)Rationalization (economics)01 natural sciences010305 fluids & plasmasHigh Energy Physics - Phenomenology (hep-ph)Square root0103 physical sciencesComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONAlgebraic number010306 general physicsMathematical PhysicsVariable (mathematics)MapleMathematical Physics (math-ph)AlgebraHigh Energy Physics - PhenomenologyHigh Energy Physics - Theory (hep-th)Hardware and ArchitectureengineeringComputer Science - Mathematical SoftwareMathematical Software (cs.MS)
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SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results

2020

The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D scans from raw incomplete data. SHARP 2020 is organised as a workshop in conjunction with ECCV 2020. There are two complementary challenges, the first one on 3D human scans, and the second one on generic objects. Challenge 1 is further split into two tracks, focusing, first, on large body and clothing regions, and, second, on fine body details. A novel evaluation metric is proposed to quantify jointly the shape reconstruction, the texture reconstruction and the amount of completed data. Additionally, two unique da…

FOS: Computer and information sciencesComputer sciencebusiness.industryComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering02 engineering and technologyTask (project management)Conjunction (grammar)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Metric (mathematics)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness
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The Essence Theory of Software Engineering – Large-Scale Classroom Experiences from 450+ Software Engineering BSc Students

2018

Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in development methods poses a challenge for software engineering education, creating a gap between education and industry. General theories such as the Essence Theory of Software Engineering can help bridge this gap by presenting software engineering students with higher-level frameworks upon which to build an understanding of software engineering methods and practical project work. In this paper, we study Essence in an educational setting to evaluate its usefuln…

FOS: Computer and information sciencesComputer sciencepracticesmedia_common.quotation_subjectohjelmistotuotantoContext (language use)02 engineering and technologyBridge (nautical)menetelmätComputer Science - Software Engineeringsoftware process engineering020204 information systems0202 electrical engineering electronic engineering information engineeringEssence Theorymedia_commoneducationbusiness.industrySEMATScale (chemistry)020207 software engineeringkäytäntöohjelmistosuunnitteluSoftware Engineering (cs.SE)koulutusWork (electrical)Software engineeringbusinessDiversity (politics)
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