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Wavelet-based Temporal Forecasting Models of Human Activities for Anomaly Detection [article]

Manuel Fernandez-Carmona, Nicola Bellotto
2020 arXiv   pre-print
Such inference is performed by a new extension of Hybrid Markov Logic Networks (HMLNs) that merges different anomaly indicators, including activity levels detected by sensors, expert rules and the new  ...  The latter in particular allow the inference system to discover deviations from long-term activity patterns, which cannot by detected by simpler frequency-based models.  ...  ACKNOWLEDGMENT The research leading to these results has received funding from the EC H2020 Programme under grant agreement No. 643691, ENRICHME.  ... 
arXiv:2002.11503v1 fatcat:g6unsn452fcqrnsxlaikkmkade

Recent trends in crowd analysis: A review

Mounir Bendali-Braham, Jonathan Weber, Germain Forestier, Lhassane Idoumghar, Pierre-Alain Muller
2021 Machine Learning with Applications  
One of the hottest topics of crowd analysis is anomaly detection. Although a unanimous definition of anomaly has not yet been met, each of crowd analysis subtopics can be subjected to abnormality.  ...  The authors discuss the performance measures used to measure the robustness and efficiency of several trackers.  ...  Their approach is made up of a Two-Stream Neural Network: 1. a spatio-temporal stream, and 2. an interactive dynamic stream.  ... 
doi:10.1016/j.mlwa.2021.100023 fatcat:kc5skiri4rho7bmnn62yaiybru

A comprehensive study of visual event computing

WeiQi Yan, Declan F. Kieran, Setareh Rafatirad, Ramesh Jain
2010 Multimedia tools and applications  
Later, we review an extensive set of papers taken from well-known conferences and journals in multiple disciplines. We analyze events, and summarize the procedure of visual event actions.  ...  We start by presenting events and their classifications, and continue with discussing the problem of capturing events in terms of photographs, videos, etc, as well as the methodologies for event storing  ...  This work was partially supported by QUB research project: Unusual event detection in audio-visual surveillance for public transport (NO.D6223EEC).  ... 
doi:10.1007/s11042-010-0560-9 fatcat:ak6u3eefefgjhmbpr7asru3n7u

Continual Learning in Neural Networks [article]

Rahaf Aljundi
2019 arXiv   pre-print
Continual machine learning aims at a higher level of machine intelligence through providing the artificial agents with the ability to learn online from a non-stationary and never-ending stream of data.  ...  We consider an infinite stream of data drawn from a non-stationary distribution with a supervisory or self-supervisory training signal.  ...  The agent is equipped with a face detector module that is detecting faces online and a multi-object face tracker.  ... 
arXiv:1910.02718v2 fatcat:7jfwt7uxl5gi3j4goz6w34qkwm

A Survey on Visual Surveillance of Object Motion and Behaviors

W. Hu, T. Tan, L. Wang, S. Maybank
2004 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
Finally, we analyze possible research directions, e.g., occlusion handling, a combination of twoand three-dimensional tracking, a combination of motion analysis and biometrics, anomaly detection and behavior  ...  Index Terms-Behavior understanding and description, fusion of data from multiple cameras, motion detection, personal identification, tracking, visual surveillance.  ...  Xu from the NLPR for their valuable suggestions and assistance in preparing this paper.  ... 
doi:10.1109/tsmcc.2004.829274 fatcat:cozxn2ogtrew3pybyuxcrj2rhi

List of Contributors [chapter]

Siddhartha Bhattacharyya, Indradip Banerjee, Shibakali Gupta
2019 Big Data Security  
Anomaly detection for such a system is a tough job [3] . That is why it is so important to do anomaly detection [4] .  ...  Hence, anomaly detection with its adaptive capabilities also can be called as adaptive thresholding, which is more intelligent than the traditional fixed threshold approach.  ...  The need for developing data-driven algorithms for creating applications on several other fields can open a new field of study.  ... 
doi:10.1515/9783110606058-202 fatcat:3jtqdtgsavas7n3vxrtbrkdbdy

Optimization of FCFS Based Resource Provisioning Algorithm for Cloud Computing

Aditya Marphatia Aditya Marphatia
2013 IOSR Journal of Computer Engineering  
We intend to create a module depicting the normal FCFS algorithm in comparison to our optimized version algorithm for resource provisioning in the cloud.  ...  Vidisha (M.P) for his great support .  ...  Anomaly Detection Systems: There have been a few approaches to anomaly intrusion detection systems, some of which are described below.  ... 
doi:10.9790/0661-1050105 fatcat:73hohpcqezf3bo6snf6la5qr64

A Survey on Wireless Indoor Localization from the Device Perspective

Jiang Xiao, Zimu Zhou, Youwen Yi, Lionel M. Ni
2016 ACM Computing Surveys  
Intrusion detection and tracking identify whether anomaly objects exist and locate them in an area of interest. Border protection prevents terrorists from entering a forbidden area.  ...  Consequently, it brings in new challenges such as anomaly detection and locating the entity.  ...  ACKNOWLEDGMENTS The authors would like to thank the anonymous reviewers and the associate editor for their valuable comments.  ... 
doi:10.1145/2933232 fatcat:5zoyp6d6knelrmkj2tx6gd4utu

Integrating Deep Learning and Augmented Reality to Enhance Situational Awareness in Firefighting Environments [article]

Manish Bhattarai
2021 arXiv   pre-print
Finally, we used a low computational unsupervised learning technique called tensor decomposition to perform meaningful feature extraction for anomaly detection in real-time.  ...  First, we used a deep Convolutional Neural Network (CNN) system to classify and identify objects of interest from thermal imagery in real-time.  ...  The last piece of this research utilizes tensor decomposition for anomaly detection and blind source separation.  ... 
arXiv:2107.11043v2 fatcat:3jm5zawelze7dhx37luja7mly4

Conference Guide [Front matter]

2020 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)  
The features are built using statistics obtained from detection and tracking results forc crowd components, i.e. individuals and their groups (any typical detectors and trackers can be used).  ...  A deep neural-network under Faster R-CNN architecture is built to detect fish from the stereo image inputs.  ...  In this paper we investigate the resilient consensus problem for multi-agent systems under the specific attack scenarios where the attacker can eavesdrop on initial information of agents among the system  ... 
doi:10.1109/icarcv50220.2020.9305477 fatcat:4h7gpoj7ljgsrlkjoyw3qcfzxi

Biomedical signal compression with time- and subject-adaptive dictionary for wearable devices

Valentina Vadori, Enrico Grisan, Michele Rossi
2016 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)  
Biometric signals compression with time-and subject-adaptive dictionary for wearable devices by Valentina Vadori Wearable devices are a leading category in the Internet of Things.  ...  The codebook is obtained and then dynamically refined in an online fashion, without requiring any prior information on the signal itself.  ...  Acknowledgements I would like to thank my supervisor Michele Rossi for his authoritative guidance through the course of these months and Roberto Francescon, Matteo Gadaleta and Mohsen Hooshmand for their  ... 
doi:10.1109/mlsp.2016.7738820 dblp:conf/mlsp/VadoriGR16 fatcat:o456gowukvd27kl5xuoqbzwppq

Visual detection of vehicles using a bag-of-features approach

Pedro Pinto, Ana Tome, Vitor Santos
2013 2013 13th International Conference on Autonomous Robot Systems  
Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective  ...  works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.  ...  e Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP -01-0124-FEDER-022701.  ... 
doi:10.1109/robotica.2013.6623539 fatcat:ialsxj53yzfkfe5f766krtkkrq

IPIN 2018 Ninth International Conference on Indoor Positioning and Indoor Navigation

2018 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN)  
SiGNAL FiNGeRPRiNT ANOMALY deTeCTiON FOR PROBABiLiSTiC iNdOOR POSiTiONiNG Key words: Indoor positioning, Fingerprinting, Error Estimates, Localisability B2.1.  ...  This information is used both in pedestrian navigation to do stationarity detection with adaptive threshold and in particle filter fusion to exclude visual data from during climbing.  ...  They naturally turned to the musicians of Ghillie's when looking for a band to collaborate with: dancers and musicians alike share a deep love for Irish culture while strongly valueing their French musical  ... 
doi:10.1109/ipin.2018.8533737 fatcat:rv5zjhjytjaijcqgvvvpmbfjfa

Decision making via semi-supervised machine learning techniques [article]

Eftychios Protopapadakis
2016 arXiv   pre-print
The primary objective is the extraction of robust inference rules. Decision support systems (DSSs) who utilize SSL have significant advantages.  ...  Such applications fields are: (a) industrial assembly lines monitoring, (b) sea border surveillance, (c) elders' falls detection, (d) transportation tunnels inspection, (e) concrete foundation piles defect  ...  These features are fed to a neural network tracker, which is capable of online adaptation.  ... 
arXiv:1606.09022v1 fatcat:zzghg6tsijgszaduo7il2rixly

Internet of Things 2.0: Concepts, Applications, and Future Directions

Ian Zhou, Imran Makhdoom, Negin Shariati, Muhammad Ahmad Raza, Rasool Keshavarz, Justin Lipman, Mehran Abolhasan, Abbas Jamalipour
2021 IEEE Access  
This cloud level AE model is redistributed to the edge devices for local anomaly detection.  ...  Hence, it decreases the time required for an expert to create a training set. The authors from [138] used federated learning to create an AE model for anomaly detection.  ... 
doi:10.1109/access.2021.3078549 fatcat:g5jkc5p6tngpfonbhtsbcjipai
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