A Japanese Tier 1 automobile manufacturing company.
Business Challenge
The client is entering in autonomous driving market. They wanted to develop a deep learning module that can recognize traffic speed limit signs in real time.
The algorithm had to be optimized on target platform for real time output.
Acclivis Contribution
CNN Layers library design and implementation.
Dataset Collection and generation.
Design and Implementation of CNN Net.
Training and Testing of CNN model.
CNN trained model generation.
Product Features Developed/Supported by Acclivis
The application performs detection and classification of the traffic speed sign detection and classification. This application uses below processing modules to perform detection
and classification:
Image Pre-processing module.
Deep Learning module
Classification module
Detection and extraction of the region of interest (i.e. Speed Sign Circle) is performed/implemented using image pre-processing modules, while Classification is performed using Deep learning module.
Project Details
Language | C and C++.
Initial development platform | NVIDIA TK1.
DL Network | CNN VGG 16 NET.
DL Network Layers | 16 Layer Network.
Deep Learning Library | Caffe.
Client Benefit
Acclivis successfully delivered deep learning based speed sign which could be integrated into the client’s existing framework.