Search Results for author:
Found 12 papers, 2 papers with code
VALD-GAN: video anomaly detection using latent discriminator augmented GAN
The most crucial and difficult challenge for intelligent video surveillance is to identify anomalies in a video that comprises anomalous behavior or occurrences.
Ranked #4 on
Anomaly Detection
on UCSD Ped2
Anomaly Detection In Surveillance Videos
Video Anomaly Detection
STemGAN: spatio-temporal generative adversarial network for video anomaly detection
Automatic detection and interpretation of abnormal events have become crucial tasks in large-scale video surveillance systems.
Ranked #5 on
Anomaly Detection
on UCSD Ped2
Anomaly Detection In Surveillance Videos
Generative Adversarial Network
+3
System Network Analytics: Evolution and Stable Rules of a State Series
We quantified stability and persistence of entity-connections in a system state series.
Enhanced Opposition Differential Evolution Algorithm for Multimodal Optimization
The optimization problem could be to minimize or maximize a given objective function and we aim to solve the maximization problems on multimodal functions in this study.
A Novel Scalable Apache Spark Based Feature Extraction Approaches for Huge Protein Sequence and their Clustering Performance Analysis
We have conducted extensive experiments on various soybean protein datasets to demonstrate the effectiveness of the proposed feature extraction methods, 60d-SPF, 6d-SCPSF, and existing feature extraction methods on SRSIO-FCM and SLFCM clustering algorithms.
Minimum Variance Embedded Auto-associative Kernel Extreme Learning Machine for One-class Classification
The experimental results show that VAAKELM consistently performs better than the existing classifiers, making it a viable alternative for the OCC task.
Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)
By using two types of Graph-Embedding, 4 variants of Graph-Embedded multi-layer KRR-based one-class classifier has been presented in this paper.
OCKELM+: Kernel Extreme Learning Machine based One-class Classification using Privileged Information (or KOC+: Kernel Ridge Regression or Least Square SVM with zero bias based One-class Classification using Privileged Information)
This privileged information is available as a feature with the dataset but only for training (not for testing).
Localized Multiple Kernel Learning for Anomaly Detection: One-class Classification
In this paper, we present a multiple kernel learning approach for the One-class Classification (OCC) task and employ it for anomaly detection.
Multi-layer Kernel Ridge Regression for One-class Classification
In this paper, a multi-layer architecture (in a hierarchical fashion) by stacking various Kernel Ridge Regression (KRR) based Auto-Encoder for one-class classification is proposed and is referred as MKOC.
On The Construction of Extreme Learning Machine for Online and Offline One-Class Classification - An Expanded Toolbox
Our proposed classifiers exhibit better performance compared to ten traditional one-class classifiers and ELM based two one-class classifiers.
Online Learning with Regularized Kernel for One-class Classification
This paper presents an online learning with regularized kernel based one-class extreme learning machine (ELM) classifier and is referred as online RK-OC-ELM.
