21,226 research outputs found
Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection
Local descriptors based on the image noise residual have proven extremely
effective for a number of forensic applications, like forgery detection and
localization. Nonetheless, motivated by promising results in computer vision,
the focus of the research community is now shifting on deep learning. In this
paper we show that a class of residual-based descriptors can be actually
regarded as a simple constrained convolutional neural network (CNN). Then, by
relaxing the constraints, and fine-tuning the net on a relatively small
training set, we obtain a significant performance improvement with respect to
the conventional detector
Lirolem: A virtual studio/Institutional Repository for the University of Lincoln
Gives an account of the Lirolem project at the University of Lincoln which was to build a repository capable of handling multimedia material as well as providing a repository for the University's research output
Analysis domain model for shared virtual environments
The field of shared virtual environments, which also
encompasses online games and social 3D environments, has a
system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model
Implementation of CAVENET and its usage for performance evaluation of AODV, OLSR and DYMO protocols in vehicular networks
Vehicle Ad-hoc Network (VANET) is a kind of Mobile Ad-hoc Network (MANET) that establishes wireless connection between cars. In VANETs and MANETs, the topology of the network changes very often, therefore implementation of efficient routing protocols is very important problem. In MANETs, the Random Waypoint (RW) model is used as a simulation model for generating node mobility pattern. On the other hand, in VANETs, the mobility patterns of nodes is restricted along the roads, and is affected by the movement of neighbour nodes. In this paper, we present a simulation system for VANET called CAVENET (Cellular Automaton based VEhicular NETwork). In CAVENET, the mobility patterns of nodes are generated by an 1-dimensional cellular automata. We improved CAVENET and implemented some routing protocols. We investigated the performance of the implemented routing protocols by CAVENET. The simulation results have shown that DYMO protocol has better performance than AODV and OLSR protocols.Peer ReviewedPostprint (published version
Autoencoder with recurrent neural networks for video forgery detection
Video forgery detection is becoming an important issue in recent years,
because modern editing software provide powerful and easy-to-use tools to
manipulate videos. In this paper we propose to perform detection by means of
deep learning, with an architecture based on autoencoders and recurrent neural
networks. A training phase on a few pristine frames allows the autoencoder to
learn an intrinsic model of the source. Then, forged material is singled out as
anomalous, as it does not fit the learned model, and is encoded with a large
reconstruction error. Recursive networks, implemented with the long short-term
memory model, are used to exploit temporal dependencies. Preliminary results on
forged videos show the potential of this approach.Comment: Presented at IS&T Electronic Imaging: Media Watermarking, Security,
and Forensics, January 201
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