On the public citation graph

Positive unlabeled learning‐based anomaly detection in videos

https://doi.org/10.1002/int.22437
0 signed · 47 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

1 of the 32 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s11042-017-5057-3 (notice 2019-06-10).

Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/asi.22621openalex-snapshot
Citation‐based bootstrapping for large‐scale author disambiguation
inferredcites →https://doi.org/10.1002/int.21891openalex-snapshot
A Road Departure Warning System Based on Video Motion Analysis and Fuzzy Logic
inferredcites →https://doi.org/10.1002/int.22161openalex-snapshot
Real‐time force doors detection system using distributed sensors and neural networks
inferredcites →https://doi.org/10.1002/int.22175openalex-snapshot
A Dempster‐Shafer theory and uninorm‐based framework of reasoning and multiattribute decision‐making for surveillance system
inferredcites →https://doi.org/10.1007/s00034-020-01522-7openalex-snapshot
Deep Multi-view Representation Learning for Video Anomaly Detection Using Spatiotemporal Autoencoders
inferredcites →https://doi.org/10.1007/s10994-019-05855-6openalex-snapshot
A survey on semi-supervised learning
inferredcites →https://doi.org/10.1007/s11042-017-5057-3openalex-snapshot
RETRACTED ARTICLE: Discovering Graphical Visual Features for Abnormal Semantic Event Detection
inferredcites →https://doi.org/10.1007/s11042-017-5244-2openalex-snapshot
Abnormal event detection for video surveillance using deep one-class learning
inferredcites →https://doi.org/10.1007/s11263-012-0594-8openalex-snapshot
Dense Trajectories and Motion Boundary Descriptors for Action Recognition
inferredcites →https://doi.org/10.1016/j.eng.2019.02.008openalex-snapshot
AED-Net: An Abnormal Event Detection Network
inferredcites →https://doi.org/10.1016/j.ipm.2019.102096openalex-snapshot
Deep ranking based cost-sensitive multi-label learning for distant supervision relation extraction
inferredcites →https://doi.org/10.1016/j.neucom.2019.08.059openalex-snapshot
Crowd anomaly detection using Aggregation of Ensembles of fine-tuned ConvNets
inferredcites →https://doi.org/10.1016/j.neucom.2019.11.087openalex-snapshot
A weakly supervised framework for abnormal behavior detection and localization in crowded scenes
inferredcites →https://doi.org/10.1016/j.patcog.2020.107515openalex-snapshot
Fast sparse coding networks for anomaly detection in videos
inferredcites →https://doi.org/10.1016/j.patcog.2020.107527openalex-snapshot
Counter-examples generation from a positive unlabeled image dataset
inferredcites →https://doi.org/10.1016/j.patrec.2013.06.010openalex-snapshot
A bagging SVM to learn from positive and unlabeled examples
inferredcites →https://doi.org/10.1093/bioinformatics/bts504openalex-snapshot
Positive-unlabeled learning for disease gene identification
inferredcites →https://doi.org/10.1109/cvpr.2005.177openalex-snapshot
Histograms of Oriented Gradients for Human Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.00803openalex-snapshot
Object-Centric Auto-Encoders and Dummy Anomalies for Abnormal Event Detection in Video
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01055openalex-snapshot
Graph Embedded Pose Clustering for Anomaly Detection
inferredcites →https://doi.org/10.1109/iccv.2013.338openalex-snapshot
Abnormal Event Detection at 150 FPS in MATLAB
inferredcites →https://doi.org/10.1109/icdm.2018.00109openalex-snapshot
Cost Effective Multi-label Active Learning via Querying Subexamples
inferredcites →https://doi.org/10.1109/icip.2018.8451831openalex-snapshot
Learning with A Generative Adversarial Network From a Positive Unlabeled Dataset for Image Classification
inferredcites →https://doi.org/10.1109/icme46284.2020.9102722openalex-snapshot
Weakly Supervised Video Anomaly Detection via Center-Guided Discriminative Learning
inferredcites →https://doi.org/10.1109/tcds.2018.2883368openalex-snapshot
Abnormal Event Detection From Videos Using a Two-Stream Recurrent Variational Autoencoder
inferredcites →https://doi.org/10.1109/tcst.2020.2997648openalex-snapshot
Data-Driven Open-Set Fault Classification of Residual Data Using Bayesian Filtering
inferredcites →https://doi.org/10.1109/tip.2019.2944306openalex-snapshot
Semi-Supervised Human Detection via Region Proposal Networks Aided by Verification
inferredcites →https://doi.org/10.1109/tmm.2018.2871421openalex-snapshot
Boosting Positive and Unlabeled Learning for Anomaly Detection With Multi-Features
inferredcites →https://doi.org/10.1109/tmm.2019.2950530openalex-snapshot
Learning Normal Patterns via Adversarial Attention-Based Autoencoder for Abnormal Event Detection in Videos
inferredcites →https://doi.org/10.1109/tnnls.2019.2892403openalex-snapshot
Large-Margin Label-Calibrated Support Vector Machines for Positive and Unlabeled Learning
inferredcites →https://doi.org/10.1109/tnnls.2019.2933554openalex-snapshot
A Deep One-Class Neural Network for Anomalous Event Detection in Complex Scenes
inferredcites →https://doi.org/10.1587/transinf.e97.d.1358openalex-snapshot
Class Prior Estimation from Positive and Unlabeled Data

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/int.22820openalex-snapshot
Learning to rank: An intelligent system for person reidentification
inferred← citeshttps://doi.org/10.1007/978-3-031-78192-6_10openalex-snapshot
Leveraging Data from Vast Unexplored Seas: Positive Unlabeled Learning for Refining Prediction Area in Good Fishing Ground Prediction
inferred← citeshttps://doi.org/10.1007/s10278-026-01951-xopenalex-snapshot
Alzheimer’s and Parkinson’s Detection with Video-Based Hybrid Deep Learning from Brain MRI
inferred← citeshttps://doi.org/10.1007/s10462-024-11092-8openalex-snapshot
Deep crowd anomaly detection: state-of-the-art, challenges, and future research directions
inferred← citeshttps://doi.org/10.1007/s10489-022-03903-8openalex-snapshot
Intelligent abnormal behavior detection using double sparseness method
inferred← citeshttps://doi.org/10.1016/j.ins.2024.120992openalex-snapshot
A multi-objective evolutionary algorithm for robust positive-unlabeled learning
inferred← citeshttps://doi.org/10.1016/j.ipm.2022.102983openalex-snapshot
Spatio-temporal graph-based CNNs for anomaly detection in weakly-labeled videos
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110872openalex-snapshot
Prime: Privacy-preserving video anomaly detection via Motion Exemplar guidance
inferred← citeshttps://doi.org/10.1016/j.oregeorev.2025.106783openalex-snapshot
A semi-supervised approach for mineral prospectivity mapping via weighted positive-unlabeled learning and tree-structured parzen estimator for hyperparameter optimization
inferred← citeshttps://doi.org/10.1109/ase63991.2025.00127openalex-snapshot
Sifting Truth from Coincidences: A Two-Stage Positive and Unlabeled Learning Model for Coincidental Correctness Detection
inferred← citeshttps://doi.org/10.1109/icais53314.2022.9742960openalex-snapshot
Temporal Features-Based Anomaly Detection from Surveillance Videos using Deep Learning Techniques
inferred← citeshttps://doi.org/10.1109/icde60146.2024.00065openalex-snapshot
A Robust Prioritized Anomaly Detection when Not All Anomalies are of Primary Interest
inferred← citeshttps://doi.org/10.1109/icdmw53433.2021.00054openalex-snapshot
Crowd behavior detection in videos using statistical physics
inferred← citeshttps://doi.org/10.1155/2023/7868415openalex-snapshot
AD‐Graph: Weakly Supervised Anomaly Detection Graph Neural Network
inferred← citeshttps://doi.org/10.3390/electronics12071517openalex-snapshot
Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.