Image segmentation, which has become a research hotspot in the field of image processing
and computer vision, refers to the process of dividing an image into meaningful and non …

Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …

Understanding the scene in which an autonomous robot operates is critical for its competent
functioning. Such scene comprehension necessitates recognizing instances of traffic …

Since the last few decades, the number of road causalities has seen continuous growth
across the globe. Nowadays intelligent transportation systems are being developed to …

In this work we address the task of semantic image segmentation with Deep Learning and
make three main contributions that are experimentally shown to have substantial practical …

Semantic segmentation is a challenging task in computer vision systems. A lot of methods
have been developed to tackle this problem ranging from autonomous vehicles, human …

We present a novel and practical deep fully convolutional neural network architecture for
semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine …

During the last half decade, convolutional neural networks (CNNs) have triumphed over
semantic segmentation, which is a core task of various emerging industrial applications such …

Semantic segmentation models gain robustness against poor lighting conditions by virtue of
complementary information from visible (RGB) and thermal images. Despite its importance …

Object segmentation requires both object-level information and low-level pixel data. This
presents a challenge for feedforward networks: lower layers in convolutional nets capture …