Search results for " Detection"
showing 10 items of 1676 documents
A Resilient Smart Architecture for Road Surface Condition Monitoring
2022
Nowadays, road surface condition monitoring is a challenging problem that cannot be addressed with traditional techniques. In this paper we propose an architecture for monitoring the condition of road surfaces based on the paradigm of Mobile Crowdsensing. First, a surface detection module extracts high level features from raw data, indicating the presence of hazards. Then, in order to make the system resilient to attacks, the system exploits a reputation module to identify malicious users and filter out unreliable data. Finally, a truth discovery module aggregates the resulting information to obtain the desired truth values. Experiments carried out on a real world dataset prove the resilien…
A genetic algorithm for the design of a fuzzy controller for active queue management
2003
Active queue management (AQM) policies are those\ud policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the\ud hosts on the network borders, and the adoption of a suitable control\ud policy. This paper proposes the adoption of a fuzzy proportional\ud integral (FPI) controller as an active queue manager for Internet\ud routers. The analytical design of the proposed FPI controller is\ud carried out in analogy with a proportional integral (PI) controller,\ud which recently has been proposed for AQM. A genetic algorithm is\ud proposed for tuning of the FPI controller parameters with respect\ud to optimal disturbance rej…
A Novel Approach for Supporting Italian Satire Detection Through Deep Learning
2021
Satire is a way of criticizing people (or ideas) by ridiculing them on political, social, and morals topics often used to denounce political and societal problems, leveraging comedic devices such as parody exaggeration, incongruity, etc.etera. Detecting satire is one of the most challenging computational linguistics tasks, natural language processing, and social multimedia sentiment analysis. In particular, as satirical texts include figurative communication for expressing ideas/opinions concerning people, sentiment analysis systems may be negatively affected; therefore, satire should be adequately addressed to avoid such systems’ performance degradation. This paper tackles automatic satire…
SpADe: Multi-Stage Spam Account Detection for Online Social Networks
2022
In recent years, Online Social Networks (OSNs) have radically changed the way people communicate. The most widely used platforms, such as Facebook, Youtube, and Instagram, claim more than one billion monthly active users each. Beyond these, news-oriented micro-blogging services, e.g., Twitter, are daily accessed by more than 120 million users sharing contents from all over the world. Unfortunately, legitimate users of the OSNs are mixed with malicious ones, which are interested in spreading unwanted, misleading, harmful, or discriminatory content. Spam detection in OSNs is generally approached by considering the characteristics of the account under analysis, its connection with the rest of …
Twitter spam account detection by effective labeling
2019
In the last years, the widespread diffusion of Online Social Networks (OSNs) has enabled new forms of communications that make it easier for people to interact remotely. Unfortunately, one of the first consequences of such a popularity is the increasing number of malicious users who sign-up and use OSNs for non-legit activities. In this paper we focus on spam detection, and present some preliminary results of a system that aims at speeding up the creation of a large-scale annotated dataset for spam account detection on Twitter. To this aim, two different algorithms capable of capturing the spammer behaviors, i.e., to share malicious urls and recurrent contents, are exploited. Experimental r…
An Evolution of the Non-Parameter Harris Affine Corner Detector: A Distributed Approach
2009
A parallel version of a new automatic Harris-based corner detector is presented. A scheduler to dynamically and homogeneously distribute high computational workload on heterogeneous parallel architectures such as Grid systems has been implemented to speedup the whole procedure. Experimental results show the robustness of the underlying scheduler, which can be easily exploited in various automatic image analysis systems.
Adaptive distributed outlier detection for WSNs.
2014
The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication com…
Embedded Knowledge-based Speech Detectors for Real-Time Recognition Tasks
2006
Speech recognition has become common in many application domains, from dictation systems for professional practices to vocal user interfaces for people with disabilities or hands-free system control. However, so far the performance of automatic speech recognition (ASR) systems are comparable to human speech recognition (HSR) only under very strict working conditions, and in general much lower. Incorporating acoustic-phonetic knowledge into ASR design has been proven a viable approach to raise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as de…
Midground Object Detection in Real World Video Scenes,
2007
Traditional video scene analysis depends on accurate background modeling to identify salient foreground objects. However, in many important surveillance applications, saliency is defined by the appearance of a new non-ephemeral object that is between the foreground and background. This midground realm is defined by a temporal window following the object's appearance; but it also depends on adaptive background modeling to allow detection with scene variations (e.g., occlusion, small illumination changes). The human visual system is ill-suited for midground detection. For example, when surveying a busy airline terminal, it is difficult (but important) to detect an unattended bag which appears…
Mean shift clustering for personal photo album organization
2008
In this paper we propose a probabilistic approach for the automatic organization of pictures in personal photo album. Images are analyzed in term of faces and low-level visual features of the background. The description of the background is based on RGB color histogram and on Gabor filter energy accounting for texture information. The face descriptor is obtained by projection of detected and rectified faces on a common low dimensional eigenspace. Vectors representing faces and background are clustered in an unsupervised fashion exploiting a mean shift clustering technique. We observed that, given the peculiarity of the domain of personal photo libraries where most of the pictures contain fa…