Suchergebnisse - autoencoder-based abnormal activity detection*

Autoencoder-based abnormal activity detection using parallelepiped spatio-temporal region von George, Michael, Jose, Babita Roslind, Mathew, Jimson, Kokare, Pranjali

“… A manual monitoring system is near impossible due to the large man-hour requirements. Recently, automatic abnormal activity detection has been an area of interest among researchers …”
Volltext

Autoencoder‐based unsupervised one‐class learning for abnormal activity detection in egocentric videos von Hu, Haowen, Hachiuma, Ryo, Saito, Hideo

“… In recent years, abnormal human activity detection has become an important research topic …”
Volltext

Ambient Sensor-based Abnormal Human Activity Detection Using Autoencoder von Kherrour, Kelthoum, Titouna, Faiza, Laskri, Mohamed Tayeb

“… Among the challenges related to human activity recognition systems that are deployed in ambient assisted living environments, is the ability to identify abnormal behavior patterns …”
Volltext

Computer Vision with Optimal Deep Stacked Autoencoder-based Fall Activity Recognition for Disabled Persons in the IoT Environment von Alabdulkreem, Eatedal, Marzouk, Radwa, Alduhayyem, Mesfer, Al-Hagery, Mohammed Abdullah, Motwakel, Abdelwahed, Hamza, Manar Ahmed

“… Artificial intelligence and Internet of Things (IoT) techniques that include deep learning and machine learning methods are now implemented in the field of medicine for automating the detection process of diseased and abnormal cases …”
Volltext

Autoencoder-Based iEEG Signal Classification for Accurate Focal and Non-focal Epilepsy Detection von Jangde, Anjali Sagar, Anuragi, Arti, Sisodia, Dilip Singh

“… Intracranial Electroencephalography (iEEG) signals capture abnormal brain neuronal activity and are widely employed in epilepsy diagnoses …”
Volltext

Abnormal activity detection using shear transformed spatio-temporal regions at the surveillance network edge von George, Michael, Jose, Babita Roslind, Mathew, Jimson

“… To detect abnormal activity, an autoencoder based method is adopted considering the requirement for running the method at the network edge …”
Volltext

Hybrid Attention and Motion Constraint for Anomaly Detection in Crowded Scenes von Zhang, Xinfeng, Fang, Jinpeng, Yang, Baoqing, Chen, Shuhan, Li, Bin

“… Since the abnormal cases are rare, variable and unpredictable, autoencoders with encoder and decoder structures using only normal samples have become a hot topic among various approaches for anomaly detection …”
Volltext

A Spatio‐Temporal Enhanced Graph‐Transformer AutoEncoder embedded pose for anomaly detection von Zhu, Honglei, Wei, Pengjuan, Xu, Zhigang

“… ‐temporal dependencies of non‐Euclidean data such as human skeleton graphs, and the autoencoder based on this basic unit is widely used to model sequence features …”
Volltext

V2AnomalyVec: Deep Discriminative Embeddings for Detecting Anomalous Activities in Surveillance Videos von Chandrakala, S., Vignesh, L. K. P.

“… existing among normal and abnormal event classes. In the case of autoencoder-based normality model trained using segments of normal events only, there may …”
Volltext

Anomaly Detection Approaches for Stock Price Manipulation Detection von Rizvi, Baqar Abbas

“… It is evident from the literature that most existing research focused on detecting a specific manipulation scheme using supervised learning but lacks the adaptive capability to capture different manipulative strategies …”
Volltext

Towards Designing Accurate Detection Methods for Emerging Cyber Threats von Yuan, Lun Pin

“… ) detection for zero-day malware before day zero, and (2) detection for habitual anomalies, assuming adversarial activities violate habitual …”
Volltext

Time-Window Group-Correlation Support vs. Individual Features: A Detection of Abnormal Users von Lun-Pin Yuan, Choo, Euijin, Yu, Ting, Issa Khalil, Zhu, Sencun

“… Autoencoder-based anomaly detection methods have been used in identifying anomalous users from large-scale enterprise logs with the assumption that adversarial activities do not follow past habitual patterns …”
Volltext

Anomaly Detection Using Predictive Convolutional Long Short-Term Memory Units von Medel, Jefferson Ryan

“… The first is an encoder decoder based model that learns spatio-temporal features from stacked non-overlapping image patches, and the second is an autoencoder based model that utilizes max-pooling …”
Volltext

Detecting human abnormal behaviour through a video generated model von Gatt, Thomas, Seychell, Dylan, Dingli, Alexiei

“… Detecting human abnormal activities is the process of observing rare events that deviate from normality …”
Volltext

Human Activity Recognition based on Stacked Autoencoder with Complex Background Conditions von Das, Aparajita, Saikia, Navajit, Rajbongshi, Subhash Ch, Sarma, Kandarpa Kumar

“… Human activity recognition is one of the prime focus areas of computer vision having a range of current and evolving applications in the real-world environment such as abnormal activity recognition …”
Volltext

Generation and Evaluation of Designs Using Deep Neural Networks von Dering, Matthew L

“… The objective of this dissertation is to reduce inefficiencies and manual tasks that are part of the product design lifecycle, using proposed deep neural …”
Volltext