Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples
under the condition that some output classes are unknown during supervised learning. To …

Meta-learning has gained wide popularity as a training framework that is more data-efficient
than traditional machine learning methods. However, its generalization ability in complex …

Generalized zero-shot learning (GZSL) aims to recognize samples whose categories may
not have been seen at training. Standard GZSL cannot handle dynamic addition of new …

We present a continual learning approach for generative adversarial networks (GANs), by
designing and leveraging parameter-efficient feature map transformations. Our approach is …

In the field of hydrology, deep learning has become a prevalent tool for runoff simulation.
However, the limitations stem from their primary focus on normality, which fails to accurately …

With the widespread application of ultrasonic guided wave (UGW) in the diagnosis of
structural damage of steel, the intelligent diagnosis based on data driven for rail damages …

Abstract Nowadays, Remote Sensing (RS) is one of the most prominent research topics in
Earth Observation. The combined use of satellite and airborne platforms for data collection …