scholarly journals Few-Shot Knowledge Transfer for Fine-Grained Cartoon Face Generation

2021 ◽  
Author(s):  
Nan Zhuang ◽  
Cheng Yang
Keyword(s):  
Knowledge Transfer ◽  
Fine Grained ◽  
Face Generation

scholarly journals Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition

2021 ◽  
Author(s):  
Bangjie Yin ◽  
Wenxuan Wang ◽  
Taiping Yao ◽  
Junfeng Guo ◽  
Zelun Kong ◽  
...  
Keyword(s):  
Face Recognition ◽  
Black Box ◽  
Fine Grained ◽  
Box Models ◽  
Meta Learning ◽  
Adversarial Examples ◽  
Adversarial Attack ◽  
Face Generation ◽  
Orbital Region ◽  
Black Box Models

Deep neural networks, particularly face recognition models, have been shown to be vulnerable to both digital and physical adversarial examples. However, existing adversarial examples against face recognition systems either lack transferability to black-box models, or fail to be implemented in practice. In this paper, we propose a unified adversarial face generation method - Adv-Makeup, which can realize imperceptible and transferable attack under the black-box setting. Adv-Makeup develops a task-driven makeup generation method with the blending module to synthesize imperceptible eye shadow over the orbital region on faces. And to achieve transferability, Adv-Makeup implements a fine-grained meta-learning based adversarial attack strategy to learn more vulnerable or sensitive features from various models. Compared to existing techniques, sufficient visualization results demonstrate that Adv-Makeup is capable to generate much more imperceptible attacks under both digital and physical scenarios. Meanwhile, extensive quantitative experiments show that Adv-Makeup can significantly improve the attack success rate under black-box setting, even attacking commercial systems.

Experiential learning for Chinese companies to complete cross-border acquisitions: the case of Chinese acquirers

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Le Wang ◽  
Lars Schweizer ◽  
Björn Michaelis
Keyword(s):  
Knowledge Transfer ◽  
Experiential Learning ◽  
Cultural Distance ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Content Type ◽  
Fine Grained ◽  
Cross Border ◽  
Foreign Acquisition ◽  
Chinese Companies

PurposeIn a contribution to the emerging research examining Chinese cross-border acquisitions (CBAs), the authors observe experiential learning applications for enhancing M&A completions. By emphasizing knowledge transfer, the authors reveal how target-to-target industry similarity and bidder-to-target cultural distance affect learning outcomes.Design/methodology/approachUsing a binary logistic regression model, the authors examine a sample of CBA attempts announced by Chinese companies from January 2002 to December 2012 to identify the variables that affect the completion of CBAs.FindingsThe authors find that foreign acquisition experience but not domestic acquisition experience enhances subsequent acquisition attempts, especially when prior and focal target companies share the dominant industrial logic. Learning transfer is negatively affected when target countries are more culturally distant from China, but learning benefits appear to increase under strong bidder-to-target cultural distance.Originality/valueBy investigating learning in the precompletion stage in Chinese outward CBAs, the authors complement research that uses postacquisition performance to assess learning. The authors’ more fine-grained characterization reveals that acquisition experience increases knowledge transfer through experiential learning. Furthermore, the authors show that dominant industrial logic and cultural distance are underexplored contextual conditions, although they interact with foreign and domestic experience to affect the completion of CBAs.

scholarly journals Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions

2019 ◽  
Author(s):  
Osaid Rehman Nasir ◽  
Shailesh Kumar Jha ◽  
Manraj Singh Grover ◽  
Yi Yu ◽  
Ajit Kumar ◽  
...  
Keyword(s):  
Fine Grained ◽  
Face Generation

Using Latent Fine-Grained Sentiment for Cross-Domain Sentiment Analysis

2021 ◽  
Vol 11 (3) ◽  
pp. 29-45
Author(s):  
Kwun-Ping Lai ◽  
Jackie Chun-Sing Ho ◽  
Wai Lam
Keyword(s):  
Knowledge Transfer ◽  
Sentiment Analysis ◽  
Real World ◽  
Coarse Grained ◽  
Target Domain ◽  
Training Strategy ◽  
Fine Grained ◽  
Cross Domain ◽  
Proposed Model ◽  
Novel Model

The authors investigate the problem task of multi-source cross-domain sentiment classification under the constraint of little labeled data. The authors propose a novel model which is capable of capturing both sentiment terms with strong or weak polarity from various source domains which are useful for knowledge transfer to unlabeled target domain. The authors propose a two-step training strategy with different granularities helping the model to identify sentiment terms with different degrees of sentiment polarity. Specifically, the coarse-grained training step captures the strong sentiment terms from the whole review while the fine-grained training step focuses on the latent fine-grained sentence sentiment which are helpful under the constraint of little labeled data. Experiments on a real-world product review dataset show that the proposed model has a good performance even under the little labeled data constraint.

Application of an image management system in microscopy

1992 ◽  
Vol 50 (2) ◽  
pp. 1052-1053
Author(s):  
Richard S. Chemock
Keyword(s):  
Data Storage ◽  
Cost Savings ◽  
Image Data ◽  
Analytical Techniques ◽  
Operational Mode ◽  
Fine Grained ◽  
Image Recording ◽  
Primary Output ◽  
Capacity Data ◽  
Image Management System

One of the most common tasks in a typical analysis lab is the recording of images. Many analytical techniques (TEM, SEM, and metallography for example) produce images as their primary output. Until recently, the most common method of recording images was by using film. Current PS/2R systems offer very large capacity data storage devices and high resolution displays, making it practical to work with analytical images on PS/2s, thereby sidestepping the traditional film and darkroom steps. This change in operational mode offers many benefits: cost savings, throughput, archiving and searching capabilities as well as direct incorporation of the image data into reports.The conventional way to record images involves film, either sheet film (with its associated wet chemistry) for TEM or PolaroidR film for SEM and light microscopy. Although film is inconvenient, it does have the highest quality of all available image recording techniques. The fine grained film used for TEM has a resolution that would exceed a 4096x4096x16 bit digital image.

Use of fractals to describe microstructures of porous thick-film platinum electrodes

1992 ◽  
Vol 50 (1) ◽  
pp. 314-315
Author(s):  
Steven D. Toteda
Keyword(s):  
Fractal Dimension ◽  
Power Plants ◽  
Electrical Response ◽  
Cubic Phase ◽  
Platinum Electrodes ◽  
Fine Grained ◽  
Impedance Response ◽  
Platinum Particles ◽  
Energy Surfaces ◽  
Highly Porous

Zirconia oxygen sensors, in such applications as power plants and automobiles, generally utilize platinum electrodes for the catalytic reaction of dissociating O2 at the surface. The microstructure of the platinum electrode defines the resulting electrical response. The electrode must be porous enough to allow the oxygen to reach the zirconia surface while still remaining electrically continuous. At low sintering temperatures, the platinum is highly porous and fine grained. The platinum particles sinter together as the firing temperatures are increased. As the sintering temperatures are raised even further, the surface of the platinum begins to facet with lower energy surfaces. These microstructural changes can be seen in Figures 1 and 2, but the goal of the work is to characterize the microstructure by its fractal dimension and then relate the fractal dimension to the electrical response. The sensors were fabricated from zirconia powder stabilized in the cubic phase with 8 mol% percent yttria. Each substrate was sintered for 14 hours at 1200°C. The resulting zirconia pellets, 13mm in diameter and 2mm in thickness, were roughly 97 to 98 percent of theoretical density. The Engelhard #6082 platinum paste was applied to the zirconia disks after they were mechanically polished ( diamond). The electrodes were then sintered at temperatures ranging from 600°C to 1000°C. Each sensor was tested to determine the impedance response from 1Hz to 5,000Hz. These frequencies correspond to the electrode at the test temperature of 600°C.

Amorphous silica coating on α-alumina particles

1995 ◽  
Vol 53 ◽  
pp. 210-211
Author(s):  
J. W. Mellowes ◽  
C. M. Chun ◽  
I. A. Aksay
Keyword(s):  
Amorphous Silica ◽  
Heterogeneous Nucleation ◽  
Homogeneous Nucleation ◽  
Silica Coating ◽  
Full Density ◽  
Optimal Conditions ◽  
Fine Grained ◽  
Alumina Particles ◽  
Complete Mullitization ◽  
Powder Compacts

Mullite (3Al2O32SiO2) can be fabricated by transient viscous sintering using composite particles which consist of inner cores of a-alumina and outer coatings of amorphous silica. Powder compacts prepared with these particles are sintered to almost full density at relatively low temperatures (~1300°C) and converted to dense, fine-grained mullite at higher temperatures (>1500°C) by reaction between the alumina core and the silica coating. In order to achieve complete mullitization, optimal conditions for coating alumina particles with amorphous silica must be achieved. Formation of amorphous silica can occur in solution (homogeneous nucleation) or on the surface of alumina (heterogeneous nucleation) depending on the degree of supersaturation of the solvent in which the particles are immersed. Successful coating of silica on alumina occurs when heterogeneous nucleation is promoted and homogeneous nucleation is suppressed. Therefore, one key to successful coating is an understanding of the factors such as pH and concentration that control silica nucleation in aqueous solutions. In the current work, we use TEM to determine the optimal conditions of this processing.

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