Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …

Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

The price of electricity on the European market is very volatile. This is due both to its mode of
production by different sources, each with its own constraints (volume of production …

Melanoma skin cancer is the most life‐threatening and fatal disease among the family of
skin cancer diseases. Modern technological developments and research methodologies …

Deep Learning techniques have been increasingly used in flood management to overcome
the limitations of accurate, yet slow, numerical models, and to improve the results of …

Change detection (CD) is essential to the accurate understanding of land surface changes
using available Earth observation data. Due to the great advantages in deep feature …

Semantic segmentation is a challenging task that addresses most of the perception needs of
intelligent vehicles (IVs) in an unified way. Deep neural networks excel at this task, as they …

Pixel-wise semantic segmentation for visual scene understanding not only needs to be
accurate, but also efficient in order to find any use in real-time application. Existing …

In this work, we propose" Residual Attention Network", a convolutional neural network using
attention mechanism which can incorporate with state-of-art feed forward network …