The world we see is ever-changing and it always changes with people, things, and the
environment. Domain is referred to as the state of the world at a certain moment. A research …

With the growing number of cars in cities, smart parking is gradually becoming a strategic
issue in building a smart city. As the precondition in smart parking, accurate parking …

Adversarial learning has achieved remarkable performances for unsupervised domain
adaptation (UDA). Existing adversarial UDA methods typically adopt an additional …

Conventional domain adaptation (DA) techniques aim to improve domain transferability by
learning domain-invariant representations; while concurrently preserving the task …

Abstract Deep Neural Networks have exhibited considerable success in various visual tasks.
However, when applied to unseen test datasets, state-of-the-art models often suffer …

Abstract Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain
gap between a labeled source dataset and an unlabelled target dataset for regression …

This study proposes a novel self‐training framework for unsupervised domain adaptation in
the segmentation of concrete wall cracks using accumulated crack data. The proposed …

Abstract Domain generalization (DG) aims to learn a model that generalizes well to unseen
target domains utilizing multiple source domains without re-training. Most existing DG works …

Abstract Domain Adaptation (DA) is always challenged by the spurious correlation between
the domain-invariant features (eg, class identity) and the domain-specific ones (eg …

Hand gesture recognition has a wide range of applications, including in the automotive and
industrial sectors, health assistive systems, authentication, and so on. Thermal images are …