Despite significant progress over the past few years, ambiguity is still a key challenge in
Facial Expression Recognition (FER). It can lead to noisy and inconsistent annotation, which …

Because the subtle differences between the different sub-categories of common visual
categories such as bird species, fine-grained classification has been seen as a challenging …

Grasp detection is a persistent and intricate challenge with various industrial applications.
Recently many methods and datasets have been proposed to tackle the grasp detection …

Fine-grained visual classification (FGVC) seeks to identify sub-classes within the same meta-
class. Prior efforts mainly mine the features of discriminative parts to enhance classification …

As computer vision continues to advance and finds widespread applications across various
domains, the need for interpretability in deep learning models becomes paramount. Existing …

Fine-grained image classification is a challenging problem in computer vision. The main
influencing factor is that similar images often have different labels, ie the inter-class similarity …

Combining data from multiple sensors to improve the overall robustness and reliability of a
classification system has become crucial in many applications, from military surveillance and …

Fine-grained visual classification task is challenging due to large variation in the
appearance of the same subcategories and similarity in the appearance of different …

Fine-Grained Visual Classification (FGVC) is a challenging task due to subtle differences
among subordinate categories. Many current FGVC approaches focus on identifying and …

Borescope image classification is an essential preprocessing step for damage detection in
aero-engines, which plays a crucial role in setting the detection threshold for later stages …