Fine-grained image recognition (FGIR) is a challenging task as it requires the recognition of
sub-categories with subtle differences. Recently, the swin transformer has shown impressive …

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 …

Motorcycle helmet detection is a crucial task in intelligent traffic systems (ITS) as it enhances
traffic safety consciousness and guides individuals towards legal compliance. Numerous …

Pests are diverse and the available datasets often contain an uneven number of examples
for different pests (aka, the long-tail distribution). This poses a great challenge to learning …

Cervical cytology is a critical screening strategy for early detection of pre-cancerous and
cancerous cervical lesions. The challenge lies in accurately classifying various cervical …

The precise recognition of vessel types is critical for applications in maritime surveillance but
manual visual inspection is slow and error-prone. Automated fine-grained object recognition …

In fine-grained image classification, there are only very subtle differences between classes.
It is challenging to learn local discriminative features and remove distractive features in fine …

Weakly-supervised fine-grained visual categorization (FGVC) aims to achieve subclass
classification within the same large class using only label information. Compared to general …

In the manufacturing industry, automatic quality inspections can lead to improved product
quality and productivity. Deep learning-based computer vision technologies, with their …

Breast Ultrasound (BUS) imaging is an essential tool for the early detection of breast cancer.
The Breast Imaging Reporting and Data System (BI-RADS) in BUS images helps …