S
Shoaib Azam
Researcher at Gwangju Institute of Science and Technology
Publications - 32
Citations - 373
Shoaib Azam is an academic researcher from Gwangju Institute of Science and Technology. The author has contributed to research in topics: Object detection & Computer science. The author has an hindex of 7, co-authored 26 publications receiving 141 citations.
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Key Points Estimation and Point Instance Segmentation Approach for Lane Detection.
TL;DR: A traffic line detection method called Point Instance Network (PINet), based on the key points estimation and instance segmentation approach, which achieves competitive accuracy and false positive on the TuSimple and Culane datasets.
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Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
TL;DR: Point Instance Network (PINet) as mentioned in this paper is a traffic line detection method based on the key points estimation and instance segmentation approach, which includes several hourglass models that are trained simultaneously with the same loss function.
Proceedings ArticleDOI
Autonomous Vehicle: The Architecture Aspect of Self Driving Car
TL;DR: The architecture of the self-driving car and its software components that include localization, detection, motion planning and mission planning are discussed and the hardware modules that are responsible for controlling the car are highlighted.
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Transfer learning for vehicle detection using two cameras with different focal lengths
TL;DR: The experimental results show that the proposed vehicle detection method can detect vehicles at a wide range of distances accurately and robustly, and significantly outperforms the baseline detection methods.
Proceedings ArticleDOI
Vehicle pose detection using region based convolutional neural network
TL;DR: This work makes use of state-of-the-art implementation of convolution neural network named the Region Based Convolutional Neural Network(FASTER-RCNN) for estimating the pose of vehicle in an image.