convolutional neural networks

biblio

Style transfer-based image synthesis as an efficient regularization technique in deep learning

Submitted by grigby1 on Fri, 12/11/2020 - 2:54pm

Resiliency
Neural networks
neural style transfer
newly created images
pubcrawl
Regularization
regularization techniques e.g
relatively poor generalization abilities
representative neural architectures
resilience
Metrics
Scalability
Skin
skin lesions
style transfer-based image synthesis
Task Analysis
Training
transfer learning
unlabeled images
Image analysis
challenging skin lesion classification case study
convolutional neural nets
convolutional neural networks
data augmentation
decision support system
deep learning
deep neural networks
Diagnosis
efficient regularization technique
base image
image classification
image classification purposes
image synthesis
labeled images
learning (artificial intelligence)
learning algorithms
Lesions
machine learning

biblio

On the Layer Choice of the Image Style Transfer Using Convolutional Neural Networks

Submitted by grigby1 on Fri, 12/11/2020 - 2:53pm

learning basis
VGG-19 neural network
VGG-19 network
texture transfer
texture information
stylistic learning
style transferred image
style transfer
Scalability
Resiliency
resilience
pubcrawl
neural style transfer
neural nets
middle layers
Metrics
color information
learning (artificial intelligence)
layer choice
implicit meaning
image texture
image style
image segmentation
image content
image colour analysis
higher layers
feature maps
feature extraction
edge detection
convolutional neural networks
color transfer

biblio

Development of Real-Time Style Transfer for Video System

Submitted by grigby1 on Fri, 12/11/2020 - 2:52pm

Scalability
optical flow
optical losses
perceptual loss
pubcrawl
real-time style transfer
real-time systems
relatively time-consuming
resilience
Resiliency
neural style transfer
Streaming media
style reconstruction loss
style transfer
video sequences
video signal processing
video style transfer
video stylization
video system
feed-forward CNN approach
artistic images
Artistic Style
computer machine
convolutional neural nets
convolutional neural networks
deep neural networks
defined time loss function
end-to-end system
fast style transformation
artificial system
feed-forward network
feedforward neural nets
high perceptual quality
Image reconstruction
Image resolution
Metrics
neural network
Neural networks

biblio

Masked Neural Style Transfer using Convolutional Neural Networks

Submitted by aekwall on Mon, 12/07/2020 - 12:09pm

feature extraction
visualization
visual perceptions
visual perception
visual experiences
VGG-19 model
Technological innovation
Semantics
object detection
masking
masked neural style transfer
Histograms
neural style transfer
face recognition
deep neural networks
convolutional neural networks
convolutional neural nets
content image
Biological neural networks
pubcrawl
Predictive Metrics
Resiliency
Scalability

biblio

Flexible Selecting of Style to Content Ratio in Neural Style Transfer

Submitted by aekwall on Mon, 12/07/2020 - 12:09pm

learning (artificial intelligence)
weight ratio selection
user defined style weight ratio
texture synthesis
style transfer
style image selection
Scalability
Resiliency
Predictive Metrics
optimization
neural style transfer
Neural networks
pubcrawl
image texture
Image color analysis
Feature Selection
feature extraction
convolutional neural networks
convolutional neural nets
convolution neural networks
convolution
content ratio
Artificial Intelligence
ART

biblio

Adversarial Examples Against Image-based Malware Classification Systems

Submitted by grigby1 on Thu, 10/29/2020 - 11:13am

learning (artificial intelligence)
visualization
Robustness
Resiliency
resilience
pubcrawl
privacy
Perturbation methods
Metrics
malware files
malware classification
malware
mal-ware classification techniques
machine learning
adversarial attack
invasive software
image-based malware classification systems
image classification
Human behavior
DL-based classification systems
data visualisation
convolutional neural networks
convolutional neural network malware classifiers
convolutional neural nets
convolution neural network
computer vision
adversarial attacks

biblio

Robustness Analysis of CNN-based Malware Family Classification Methods Against Various Adversarial Attacks

Submitted by grigby1 on Thu, 10/29/2020 - 11:12am

image-based classification methods
security
Robustness
Resiliency
resilience
pubcrawl
privacy
Microsoft malware dataset
Metrics
malware family classification
malware classification
malware
invasive software
input image
imperceptible nonrandom perturbations
adversarial attacks
image colour analysis
Image color analysis
image classification
Human behavior
feature extraction
convolutional neural networks
convolutional neural network-based malware family classification methods
convolutional neural nets
Conferences
CNN-based malware family classification method
CNN-based classification methods
Analytical models
adversarial example

biblio

Convolutional Neural Networks as Classification Tools and Feature Extractors for Distinguishing Malware Programs

Submitted by grigby1 on Thu, 10/29/2020 - 11:11am

malware detection
visualization
Training
testing
SVM
Support vector machines
support vector machine
Resiliency
resilience
pubcrawl
privacy
pattern classification
nearest neighbour methods
microsoft malware classification challenge
Metrics
malware programs
anti-malware industry
malware classification
malware
learning (artificial intelligence)
KNN
k-nearest neighbors
invasive software
Human behavior
feature extractors
feature extraction
convolutional neural networks
convolutional neural nets
computer architecture
computationally efficient CNN-based architecture
CNN based algorithms
classification tools

biblio

An Internet of Vehicles Intrusion Detection System Based on a Convolutional Neural Network

Submitted by aekwall on Mon, 10/19/2020 - 11:48am

Internet of Vehicle
wireless sensor networks
vehicular ad hoc networks
telecommunication traffic
security issues
Resiliency
pubcrawl
packet header analysis
network attacks
Metrics
low-powered embedded vehicle terminal
Kernel
Intrusion Detection System (IDS)
Intrusion Detection
Internet of Vehicles intrusion detection system
Internet of Vehicles
automobiles
internet
information security
IDS
Human Factors
Human behavior
feature extraction
cyber physical systems
Cryptography
convolutional neural networks
convolutional neural network (CNN)
convolutional neural network
convolutional neural nets
convolution
computer network security
car network

biblio

Dynamic Adaptation of Approximate Bit-width for CNNs based on Quantitative Error Resilience

Submitted by grigby1 on Tue, 10/06/2020 - 1:40pm

dynamic adaptation
Resiliency
resilience
quantitative error resilience
pubcrawl
Power demand
power consumption
power aware computing
Neurons
logic circuits
Hardware
error resilience
dynamic adaptation of approximate bit-width
adders
convolutional neural networks
convolutional neural network
convolutional neural nets
convolution
configurable adder
Computing Theory
CNNs
approximation theory
approximate computing technology
approximate computing
approximate bit-width

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Cyber-Physical Systems Virtual Organization

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

convolutional neural networks

Style transfer-based image synthesis as an efficient regularization technique in deep learning

On the Layer Choice of the Image Style Transfer Using Convolutional Neural Networks

Development of Real-Time Style Transfer for Video System

Masked Neural Style Transfer using Convolutional Neural Networks

Flexible Selecting of Style to Content Ratio in Neural Style Transfer

Adversarial Examples Against Image-based Malware Classification Systems

Robustness Analysis of CNN-based Malware Family Classification Methods Against Various Adversarial Attacks

Convolutional Neural Networks as Classification Tools and Feature Extractors for Distinguishing Malware Programs

An Internet of Vehicles Intrusion Detection System Based on a Convolutional Neural Network

Dynamic Adaptation of Approximate Bit-width for CNNs based on Quantitative Error Resilience