Efficient Neural Network For Real Semantic Segmentation

Abstract

At present we have the research innovations that can viably empowers the driver to keep away from smashing regardless. Advance driving assistance system (ADAS) enables autonomous vehicle to transform into a reality. One of the essential advancements of ADAS is semantic segmentation and we are witnessing fundamentally in semantic segmentation generally by the virtue of deep learning. The ability to play out the pixel wise image segmentation progressively is of the principal significance in ADAS applications. The goal of semantic segmentation is to identify the exact region that the object occupies. In this proposed work ENet (efficient neural network) model is used for semantic segmentation for a superior scene understanding and then we are dissecting the execution of this model by doing hyper-parameter tuning.