Skip to main navigation
Skip to search
Skip to main content
Universitas Indonesia Home
Home
Profiles
Research units
Research output
Equipments
Projects
Activities
Press/Media
Search by expertise, name or affiliation
Embedded Deep Learning System for Classification of Car Make and Model
Ari Wibisono
Department of Computer Science
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Embedded Deep Learning System for Classification of Car Make and Model'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Area under the Receiver Operating Characteristic (AUROC)
100%
Neural Network Method
100%
Embedded Systems
100%
Deep Learning System
100%
Embedded Deep Learning
100%
Urban Areas
50%
Classification Model
50%
Convolutional Neural Network
50%
Computation Time
50%
Machine Learning
50%
Image Processing
50%
Success Rate
50%
Systems Approach
50%
Time-dependent Simulation
50%
Evaluation Metrics
50%
InceptionV3
50%
U-Net
50%
DenseNet
50%
Support Activities
50%
Intelligent Traffic System
50%
NASNet
50%
Traffic Information Collection
50%
Car Recognition
50%
Collection Statistics
50%
Automatic Car
50%
Concurrent Users
50%
Computer Science
Neural Network
100%
Learning System
100%
Deep Learning Method
100%
Embedded System
100%
Classification Models
50%
Image Processing
50%
Convolutional Neural Network
50%
Computational Time
50%
Evaluation Metric
50%
Simulation Time
50%
Inception V3
50%
Residual Neural Network
50%
DenseNet
50%
Traffic Information
50%
Support Activity
50%
Concurrent User
50%
Machine Learning
50%