Abstract:
This paper proposes a deep learning-based efficient and compact solution for road scene segmentation problem, named Deep Residual Coalesced Convolutional Network (RCC-Net...Show MoreMetadata
Abstract:
This paper proposes a deep learning-based efficient and compact solution for road scene segmentation problem, named Deep Residual Coalesced Convolutional Network (RCC-Net). Initially, the RCC-Net performs dimensionality reduction to compress and extract relevant features, from which it is subsequently delivered to the encoder. The encoder adopts the residual network style for efficient model size. In the core of each residual network, three different convolutional layers are simultaneously coalesced for obtaining broader information. The decoder is then altered to up sample the encoder for pixel-wise mapping from the input images to the segmented output. Experimental results reveal the efficacy of the proposed network over the-state-of-the-art methods and its capability to be deployed in an average system.
Date of Conference: 08-12 May 2017
Date Added to IEEE Xplore: 20 July 2017
ISBN Information: