Skip to main navigation
Skip to search
Skip to main content
Illinois Experts Home
LOGIN & Help
Link opens in a new tab
Search content at Illinois Experts
Home
Profiles
Research units
Research & Scholarship
Datasets
Honors
Press/Media
Activities
House style recognition using deep convolutional neural network
Yun Kyu Yi
, Yahan Zhang
, Junyoung Myung
School of Architecture
Center for East Asian and Pacific Studies
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'House style recognition using deep convolutional neural network'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Computer Science
Architectural Style
100%
Deep Convolutional Neural Networks
100%
Natural Language Processing
50%
Speech Recognition
50%
Neural Network Model
50%
Face Recognition
50%
Conventional Method
50%
Object Recognition
50%
Recognition Algorithm
50%
Esthetic Preference
50%
Convolutional Neural Network
50%
Deep Learning Method
50%
Architectural Design
50%
Keyphrases
Image Recognition
100%
Deep Convolutional Neural Network (deep CNN)
100%
House Style
100%
Style Recognition
100%
Architectural Style
40%
Image Data
20%
Architectural Design
20%
Speech Recognition
20%
Face Recognition
20%
Training Model
20%
Natural Language Processing
20%
Object Identification
20%
Deep Learning
20%
Art Image
20%
Aesthetic Preference
20%
Convolutional Neural Network Model
20%
Image Recognition Algorithms
20%
Engineering
Image Recognition
100%
House Style
100%
Convolutional Neural Network
100%
Limitations
16%
Network Model
16%
Conventional Method
16%
Natural Language Processing
16%
Object Recognition
16%
Deep Learning Method
16%
Architectural Design
16%