Video tampering dataset development in temporal domain for video forgery authentication

This chapter models the relation between temporal aspect (run for an hour vs. *run all the way to the store for an hour) and spatial aspect (meander for a mile vs. *end for a mile) previously discussed by Gawron (2009). The chapter shows that for-adverbials impose analogous conditions on the spatial domain and on the temporal domain, and that an event may satisfy stratified reference with respect to one of the domains without satisfying it with respect to the other one as well. This provides the means to extend the telic-atelic opposition to the spatial domain. The chapter argues in some detail that stratified reference is in this respect empirically superior to an alternative view of telicity based on divisive reference (Krifka 1998).

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Two different temporal domain integration schemes combined with compact finite difference method to solve modified Burgers’ equation

Ain Shams Engineering Journal ◽

10.1016/j.asej.2021.05.021 ◽

2021 ◽

Author(s):

Ravneet Kaur ◽

Shallu ◽

V.K. Kukreja ◽

Nabendra Parumasur ◽

Pravin Singh

Keyword(s):

Finite Difference ◽

Finite Difference Method ◽

Difference Method ◽

Burgers Equation ◽

Compact Finite Difference ◽

Compact Finite Difference Method ◽

Integration Schemes ◽

Temporal Domain ◽

Modified Burgers Equation ◽

Domain Integration

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MesoNet: a Compact Facial Video Forgery Detection Network

2018 IEEE International Workshop on Information Forensics and Security (WIFS) ◽

10.1109/wifs.2018.8630761 ◽

2018 ◽

Cited By ~ 82

Author(s):

Darius Afchar ◽

Vincent Nozick ◽

Junichi Yamagishi ◽

Isao Echizen

Keyword(s):

Forgery Detection ◽

Video Forgery Detection ◽

Video Forgery

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MODEL-FREE FUNCTIONAL MRI ANALYSIS USING TOPOGRAPHIC INDEPENDENT COMPONENT ANALYSIS

International Journal of Neural Systems ◽

10.1142/s0129065704002017 ◽

2004 ◽

Vol 14 (04) ◽

pp. 217-228 ◽

Cited By ~ 7

Author(s):

ANKE MEYER-BÄSE ◽

OLIVER LANGE ◽

AXEL WISMÜLLER ◽

HELGE RITTER

Keyword(s):

Independent Component Analysis ◽

Slight Modification ◽

Component Analysis ◽

Independent Component ◽

Self Organizing Map ◽

Analysis Techniques ◽

Model Free ◽

Temporal Domain ◽

Different Types ◽

Fmri Analysis

Data-driven fMRI analysis techniques include independent component analysis (ICA) and different types of clustering in the temporal domain. Since each of these methods has its particular strengths, it is natural to look for an approach that unifies Kohonen's self-organizing map and ICA. This is given by the topographic independent component analysis. While achieved by a slight modification of the ICA model, it can be at the same time used to define a topographic order (clusters) between the components, and thus has the usual computational advantages associated with topographic maps. In this contribution, we can show that when applied to fMRI analysis it outperforms FastICA.

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Order in Space: A General Formalism for Spatial Reasoning

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213097000232 ◽

1997 ◽

Vol 06 (04) ◽

pp. 423-450 ◽

Cited By ~ 11

Author(s):

Baher A. El-Geresy ◽

Alia I. Abdelmoty

Keyword(s):

Space Dimension ◽

Spatial Reasoning ◽

Spatial Information ◽

Spatial Objects ◽

Temporal Domain ◽

Spatial Information Systems ◽

Connected Set ◽

General Constraints ◽

Different Types ◽

Composition Table

In this paper we propose a general approach for reasoning in space. The approach is composed of a set of two general constraints to govern the spatial relationships between objects in space, and two rules to propagate relationships between those objects. The approach is based on a novel representation of the topology of the space as a connected set of components using a structure called adjacency matrix which can capture the topology of objects of different complexity in any space dimension. The formalism is used to explain spatial compositions resulting in indefinite and definite relations and it is shown to be applicable to reasoning in the temporal domain. The main contribution of the formalism is that it provides means for constructing composition tables for objects with arbitrary complexity in any space dimension. A new composition table between spatial objects of different types is presented. A major advantage of the method is that reasoning between objects of any complexity can be achieved in a defined limited number of steps. Hence, the incorporation of spatial reasoning mechanisms in spatial information systems becomes possible.

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