scholarly journals Dynamic Inconsistency-aware DeepFake Video Detection

2021 ◽  
Author(s):  
Ziheng Hu ◽  
Hongtao Xie ◽  
YuXin Wang ◽  
Jiahong Li ◽  
Zhongyuan Wang ◽  
...  
Keyword(s):  
Information Security ◽  
Detection Methods ◽  
Dynamic Inconsistency ◽  
Robust Detection ◽  
Structure Similarity ◽  
Critical Regions ◽  
Global And Local ◽  
Inter Frame ◽  
Cross Reference ◽  
Local Perspectives

The spread of DeepFake videos causes a serious threat to information security, calling for effective detection methods to distinguish them. However, the performance of recent frame-based detection methods become limited due to their ignorance of the inter-frame inconsistency of fake videos. In this paper, we propose a novel Dynamic Inconsistency-aware Network to handle the inconsistent problem, which uses a Cross-Reference module (CRM) to capture both the global and local inter-frame inconsistencies. The CRM contains two parallel branches. The first branch takes faces from adjacent frames as input, and calculates a structure similarity map for a global inconsistency representation. The second branch only focuses on the inter-frame variation of independent critical regions, which captures the local inconsistency. To the best of our knowledge, this is the first work to totally use the inter-frame inconsistency information from the global and local perspectives. Compared with existing methods, our model provides a more accurate and robust detection on FaceForensics++, DFDC-preview and Celeb-DFv2 datasets.

Concordant Exploration of the Kinetics of RNA Folding from Global and Local Perspectives

2006 ◽  
Vol 355 (2) ◽  
pp. 282-293 ◽  
Author(s):  
Lisa W. Kwok ◽  
Inna Shcherbakova ◽  
Jessica S. Lamb ◽  
Hye Yoon Park ◽  
Kurt Andresen ◽  
...  
Keyword(s):  
Rna Folding ◽  
Global And Local ◽  
Kinetics Of ◽  
Local Perspectives

The dialectic between global and local perspectives in archaeological theory, heritage and publications

2008 ◽  
Vol 15 (1) ◽  
pp. 56-69 ◽  
Author(s):  
Kristian Kristiansen
Keyword(s):  
Annual Meeting ◽  
The Other ◽  
Archaeological Theory ◽  
Common Trends ◽  
Archaeological Practice ◽  
The Past ◽  
Other Hand ◽  
Legislative Framework ◽  
Global And Local ◽  
Local Perspectives

When I agreed to present the article as a vehicle for discussion at a session at the EAA's annual meeting in Zadar, Croatia, I decided to approach the question of a European archaeology from what I considered to be the three organizing pillars of archaeological practice: heritage, theory and publications. Heritage is the dominant organizational/legislative framework for archaeological practice, and it is where most of the money is spent. Theory, on the other hand, organizes most of our interpretations of the past, while publications are still the most common way of presenting the results of both heritage work (mostly excavations) and interpretations of that work. In this way I hoped to have encircled the dominant parameters for a diagnosis of the archaeological landscapes in Europe. I assumed that there might be some correlation between the three, and that such observed common trends within two or more variables would strengthen the argument, to paraphrase processual jargon.

scholarly journals Fault Detection Method Based on Global-Local Marginal Discriminant Preserving Projection for Chemical Process

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 122
Author(s):  
Yang Li ◽  
Fangyuan Ma ◽  
Cheng Ji ◽  
Jingde Wang ◽  
Wei Sun
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Chemical Process ◽  
Detection Method ◽  
Detection Performance ◽  
Detection Methods ◽  
Normal Operation ◽  
Discriminative Feature ◽  
Inherent Feature ◽  
Global And Local

Feature extraction plays a key role in fault detection methods. Most existing methods focus on comprehensive and accurate feature extraction of normal operation data to achieve better detection performance. However, discriminative features based on historical fault data are usually ignored. Aiming at this point, a global-local marginal discriminant preserving projection (GLMDPP) method is proposed for feature extraction. Considering its comprehensive consideration of global and local features, global-local preserving projection (GLPP) is used to extract the inherent feature of the data. Then, multiple marginal fisher analysis (MMFA) is introduced to extract the discriminative feature, which can better separate normal data from fault data. On the basis of fisher framework, GLPP and MMFA are integrated to extract inherent and discriminative features of the data simultaneously. Furthermore, fault detection methods based on GLMDPP are constructed and applied to the Tennessee Eastman (TE) process. Compared with the PCA and GLPP method, the effectiveness of the proposed method in fault detection is validated with the result of TE process.

scholarly journals Enhancing Intelligent Anemia Detection via Unifying Global and Local Views of Conjunctiva Image with Two-Branch Neural Networks

2022 ◽  
Author(s):  
Lijuan Zheng ◽  
Shaopeng Liu ◽  
Senping Tian ◽  
Jianhua Guo ◽  
Xinpeng Wang ◽  
...  
Keyword(s):  
Network Architecture ◽  
Clinical Symptoms ◽  
Detection Methods ◽  
Testing Methods ◽  
Neural Network Architecture ◽  
Real World Application ◽  
Algorithmic Framework ◽  
Comparable Accuracy ◽  
Global And Local ◽  
Detection Effect

Abstract Anemia is one of the most widespread clinical symptoms all over the world, which could bring adverse effects on people's daily life and work. Considering the universality of anemia detection and the inconvenience of traditional blood testing methods, many deep learning detection methods based on image recognition have been developed in recent years, including the methods of anemia detection with individuals’ images of conjunctiva. However, existing methods using one single conjunctiva image could not reach comparable accuracy in anemia detection in many real-world application scenarios. To enhance intelligent anemia detection using conjunctiva images, we proposed a new algorithmic framework which could make full use of the data information contained in the image. To be concrete, we proposed to fully explore the global and local information in the image, and adopted a two-branch neural network architecture to unify the information of these two aspects. Compared with the existing methods, our method can fully explore the information contained in a single conjunctiva image and achieve more reliable anemia detection effect. Compared with other existing methods, the experimental results verified the effectiveness of the new algorithm.

Analyzing China’s Provincial Environmental Emissions and Its Influencing Factors: A Spatial Analysis

2021 ◽  
Author(s):  
Xing Wang ◽  
Dequn Zhou
Keyword(s):  
Spatial Analysis ◽  
Spatial Dependence ◽  
Transmission Mechanism ◽  
Level Data ◽  
Environmental Emissions ◽  
Per Capita ◽  
Global And Local ◽  
Province Level ◽  
Local Perspectives ◽  
Spatial Transmission

Abstract In-depth analyses of the spatial heterogeneity in environmental emissions, and the causes of differences are of great importance for contributing to provide reference for reduction policies. However, a spatial analysis of the existence and mechanism of China’s environmental emissions is still ignored. Using the province-level data of thirty provinces in China over 2005-2017, this paper constructs a spatial Durbin model (SDM) to empirically address the existence and spatial transmission mechanism of environmental emissions. The main results are as follows: first, China’s environmental emissions show significant characteristics of spatial dependence and clustering from global and local perspectives, indicating that the existence of spatial autocorrelation in environmental emissions across regions. Second, both per capita GDP and urbanization have positive impacts on environmental emissions, but the impacts of environmental regulation and FDI are insignificant. Third, urbanization not only directly influences environmental emissions, but also indirectly influences environmental emissions. Our analysis provides valuable information for developing policies to effectively alleviate pollution.

Intrusion Prevention System

2016 ◽  
pp. 245-258
Author(s):  
Bijaya Kumar Panda ◽  
Manoranjan Pradhan ◽  
Sateesh Kumar Pradhan
Keyword(s):  
Information Security ◽  
Information Sharing ◽  
Rapid Growth ◽  
Detection Methods ◽  
Intrusion Prevention ◽  
Unauthorized Access ◽  
Prevention System ◽  
Intrusion Prevention Systems ◽  
Intrusion Prevention System ◽  
Use Of Internet

In the last decade, there is a rapid growth in the use of Internet by the organization for information sharing. As information is very vital to the organizations, it should be preserved and insulated from any unauthorized access or alternation. In last few years, attacks on the computer infrastructures have increased exponentially. Several information security techniques are available now a days like firewalls, anti-virus software and Intrusion prevention systems (IPSs), which are important tools for protecting an organization from intrusions. Now most attacks are impossible to defend with firewalls and anti-virus software alone. Without an IPS, such attacks are difficult to detect and prevent. This chapter presents different definitions of intrusion prevention system with meaningful explanation; compare network IPS with Host IPS, common and the advanced detection methods, common IPS components, coverage of attacks by IPS and criteria to select right IPS. Finally, this chapter concludes with an analysis of the challenges that still remain to be resolved.

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