Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

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 …

Abstract Spiking Neural Networks (SNNs) have gained huge attention as a potential energy-
efficient alternative to conventional Artificial Neural Networks (ANNs) due to their inherent …

Deep learning has been acknowledged as being robust in managing and controlling the
performance of construction safety. However, there is an absence of state-of-the-art review …

Spiking neural networks (SNNs) that mimic information transmission in the brain can energy-
efficiently process spatio-temporal information through discrete and sparse spikes, thereby …

In recent years, the remote sensing image (RSI) semantic segmentation attracts increasing
research interest due to its wide application. RSIs are difficult to be processed holistically on …

Abstract Deep Neural Networks have received considerable attention in recent years. As the
complexity of network architecture increases in relation to the task complexity, it becomes …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

High-resolution representations (HR) are essential for dense prediction tasks such as
segmentation, detection, and pose estimation. Learning HR representations is typically …

Semantic image segmentation, the process of classifying each pixel in an image into a
particular class, plays an important role in many visual understanding systems. As the …