Fine-grained search task such as retrieving subordinate categories of birds, dogs or cars,
has been an important but challenging problem in computer vision. Although many effective …

The perception of the complex road environment is a critical factor in autonomous driving,
which has become the research focus in intelligent vehicles. In this paper, a real-time front …

Parameter-Efficient Tuning (PET) has emerged as a leading advancement in both Natural
Language Processing and Computer Vision, enabling efficient accommodation of …

The ability to identify urban locations with a high risk of diseases infections is a central
aspect of public policies aiming at controlling these diseases. In this paper, we investigate …

Cloud Computing has emerged as a viable alternative to in-house computing resources for
many organisations. It offers an alternative solution for many enterprise applications …

In response to the challenges posed by the extensive parameter updates required for full
fine-tuning of large-scale pre-trained models, parameter-efficient fine-tuning (PEFT) …

Transfer learning has made significant advancements, however, the issue of overfitting
continues to pose a major challenge. Data augmentation has emerged as a highly …

Estimating the per-capita income and the household income at a fine-grained geographical
scale is critical but challenging, even across the developed economies. In this article, a …

The high specificity of classes in fine-grained clas-sification tasks leads to a small number of
images per class in the common research datasets. Thus, the intra-class variance, such as …

An essential task for computer vision-based assistive technologies is to help visually
impaired people to recognize objects in constrained environments, for instance, recognizing …