Browsing Fakultet for informasjonsteknologi og elektroteknikk (IE) by Journals "Neurocomputing"
Now showing items 1-6 of 6
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Anomalous entities detection and localization in pedestrian flows
(Journal article; Peer reviewed, 2018)We propose a novel Gaussian kernel based integration model (GKIM) for anomalous entities detection and localization in pedestrian flows. The GKIM integrates spatio-temporal features for efficient and robust motion ... -
Classification of long sequential data using circular dilated convolutional neural networks
(Peer reviewed; Journal article, 2023)Classification of long sequential data is an important Machine Learning task and appears in many application scenarios. Recurrent Neural Networks, Transformers, and Convolutional Neural Networks are three major techniques ... -
Density independent hydrodynamics model for crowd coherency detection
(Journal article; Peer reviewed, 2017)We propose density independent hydrodynamics model (DIHM) which is a novel and automatic method for coherency detection in crowded scenes. One of the major advantages of the DIHM is its capability to handle changing density ... -
Enabling automation and edge intelligence over resource constraint IoT devices for smart home
(Peer reviewed; Journal article, 2022)Smart home applications are pervasive and have gained popularity due to the overwhelming use of Internet of Things (IoT). The revolution in IoT technologies made homes more convenient, efficient and perhaps more secure. ... -
Geolocation estimation of target vehicles using image processing and geometric computation
(Journal article; Peer reviewed, 2022)Estimating vehicles’ locations is one of the key components in intelligent traffic management systems (ITMSs) for increasing traffic scene awareness. Traditionally, stationary sensors have been employed in this regard. The ... -
A step-by-step training method for multi generator GANs with application to anomaly detection and cybersecurity
(Peer reviewed; Journal article, 2023)Cyber attacks and anomaly detection are problems where the data is often highly unbalanced towards normal observations. Furthermore, the anomalies observed in real applications may be significantly different from the ones ...