object detection

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Physical Adversarial Examples for Image Classifiers and Object Detectors

Submitted by akarns on Thu, 09/27/2018 - 8:35am. Contributor:

Ivan Evtimov

BIO

Adversarial Machine Learning
object detection
road signs
classifiers
adversarial examples
Posters
Poster

biblio

An evaluation of region based object detection strategies within X-ray baggage security imagery

Submitted by grigby1 on Thu, 06/07/2018 - 2:03pm

security
policy-based governance
Policy-Governed Secure Collaboration
Proposals
pubcrawl
R-CNN/R-FCN variants
region based object detection
resilience
Resiliency
ResNet-101
Policy
sliding window driven CNN approach
SWCNN
Task Analysis
transfer learning
VGG16
Weapons
X-ray baggage security
X-ray baggage security imagery
X-ray imaging
image classification
cluttered X-ray security imagery
collaboration
convolution
cyber physical systems
deep learning
Faster Region-based CNN
feature extraction
first-stage region proposal
Fully Convolutional Networks
class firearm detection problem
ImageNet dataset
learning (artificial intelligence)
Metrics
microsoft windows
neural nets
neural networks security
object class X-ray detection problem
object detection
object localization strategies

biblio

Incremental knowledge acquisition and self-learning for autonomous video surveillance

Submitted by K_Hooper on Wed, 04/04/2018 - 8:56am

unlabeled video streams
knowledge acquisition
object detection
pubcrawl
Resiliency
safety purpose
Scalability
self-learning
Self-Organizing Maps
standard machine learning pipelines
Intelligent Video Analysis
Unsupervised Learning
unsupervised machine learning
video feed
video frame
video signal processing
video stream
video streaming
video surveillance
video surveillance systems
Hazards
Anomaly Detection
autonomous video surveillance
benchmark video dataset
Change detection
Clustering algorithms
cognition
event detection
feature extraction
hazard detection
action recognition
Heuristic algorithms
Human behavior
imperative security
incremental knowledge acquisition
incremental learning
incremental machine learning
Industry 4.0
industry/smart factory settings
intelligent high-level video analysis

biblio

Human Detection and Tracking for Video Surveillance: A Cognitive Science Approach

Submitted by K_Hooper on Wed, 04/04/2018 - 8:56am

image classification
visualization
visual saliency
video surveillance
video sequences
Support vector machines
Scalability
saliency prediction model
Resiliency
pubcrawl
Prediction algorithms
positively detected windows
object detection
k-means algorith
Clustering algorithms
human tracking
human resources
human detection
human being detection
Human behavior
HOG feature vectors
histograms of oriented gradients
feature extraction
deep multilevel network
computer vision algorithms
computer vision
Computational modeling
cognitive science approach

biblio

Fully Automatic, Real-Time Vehicle Tracking for Surveillance Video

Submitted by K_Hooper on Wed, 04/04/2018 - 8:56am

object tracking
video surveillance
video signal processing
traffic surveillance videos
traffic engineering computing
state-of-the-art trackers
Scalability
Resiliency
real-world object variation
real-time vehicle tracking
pubcrawl
Optical variables measurement
Optical imaging
object tracking framework
Adaptive optics
object detection
Noise measurement
multiple unstable video
manual initialization
lighting
image sequences
illumination conditions
Human behavior
fully automatic vehicle tracking
Detectors
automatic tracker initialization
automatic object tracking system

biblio

Dynamic clustering for event detection and anomaly identification in video surveillance

Submitted by K_Hooper on Wed, 04/04/2018 - 8:56am

Normal Plane
video surveillance event
video surveillance
video signal processing
Trajectory
Time variant events
spectral clustering
Scalability
Roads
Resiliency
pubcrawl
Pattern recognition
object detection
Anomaly Identification
life video surveillance
learning (artificial intelligence)
human behavioral patterns
Human behavior
Heuristic algorithms
feature extraction
event detection
dynamic clustering
Clustering algorithms
Anomaly Plane
anomaly identification results

biblio

Moving Target Defense Intrusion Detection System for IPv6 based smart grid advanced metering infrastructure

Submitted by K_Hooper on Wed, 02/28/2018 - 10:39am

Ports (Computers)
Training
static based attack detection techniques
smart power grids
smart meters
Smart Grids
smart grid IPv6 based advanced metering infrastructure
smart grid communications
smart grid advanced metering infrastructure
Smart Grid
security of data
Routing
Resiliency
pubcrawl
power system measurement
collaboration
Planar Key
object detection
network traffic
moving target defense intrusion detection system
moving target defense
Metrics
MATLAB
ipv6 security
IP networks
Intrusion Detection Systems
Intrusion Detection
Difference Plane
composability

biblio

Physical security assessment with convolutional neural network transfer learning

Submitted by K_Hooper on Wed, 02/14/2018 - 10:59am

security of data
physical security
physical security assessment
physical security system
physical security video data
pubcrawl
Resiliency
Scalability
security
Periodic retraining
Support vector machines
target detection
Training
Training data
transfer learning
video signal processing
visible imager data
artificial intelligence security
object recognition tasks
Object recognition
object detection
Nuisance Alarms
neural nets
Metrics
machine learning
learning (artificial intelligence)
human in the loop ground truth data
Human behavior
feature extraction
deep learning techniques
convolutional neural network transfer learning
convolutional neural network
Artificial Neural Networks

biblio

Target Tracking Optimization of UAV Swarms Based on Dual-Pheromone Clustering

Submitted by grigby1 on Tue, 02/06/2018 - 1:05pm

surveillance result propagation
Aircraft
wireless communication interface
Unmanned Aerial Vehicles
UAV swarm
UAV network connectivity
temporarily invisible targets
target tracking optimization
target tracking
target detection
ant colony optimisation
surveillance mission
surveillance
stable overlay network
Resiliency
repulsive pheromones
object detection
reconnaissance mission
pubcrawl
pattern clustering
data sharing
Network reconnaissance
multihop clustering
multi-robot systems
map coverage performance
dual-pheromone clustering hybrid approach
dual-pheromone ant-colony model
DPCHA
disappearing target model
autonomous aircraft
autonomous aerial vehicles
coverage fairness
connection volatility
communication range
collaborative swarm
Clustering algorithms
cluster stability
Base stations
attractive pheromones
Atmospheric modeling

biblio

Active surveillance using depth sensing technology \#8212; Part I: Intrusion detection

Submitted by grigby1 on Mon, 11/20/2017 - 11:05am

outdoor intrusion activities
wall climbing detection
video surveillance
Streaming media
skeletal trespassing detection
skeletal position monitoring
sensors
safety systems
Resiliency
real-time systems
pubcrawl
premise intrusion
active surveillance
object detection
Microsoft Kinect sensor
Metrics
loitering detection
Intrusion Detection
image sensors
Human Factors
Human behavior
depth sensing technology
computer architecture

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Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

object detection

Physical Adversarial Examples for Image Classifiers and Object Detectors

An evaluation of region based object detection strategies within X-ray baggage security imagery

Incremental knowledge acquisition and self-learning for autonomous video surveillance

Human Detection and Tracking for Video Surveillance: A Cognitive Science Approach

Fully Automatic, Real-Time Vehicle Tracking for Surveillance Video

Dynamic clustering for event detection and anomaly identification in video surveillance

Moving Target Defense Intrusion Detection System for IPv6 based smart grid advanced metering infrastructure

Physical security assessment with convolutional neural network transfer learning

Target Tracking Optimization of UAV Swarms Based on Dual-Pheromone Clustering

Active surveillance using depth sensing technology \#8212; Part I: Intrusion detection