The task of fine-grained visual classification (FGVC) is to distinguish targets from
subordinate classifications. Since fine-grained images have the inherent characteristic of …

Rapid advancements in technology, particularly in soil tools and agricultural machinery,
have led to the proliferation of mechanized agriculture. The interaction between such …

Plant leaf identification is an important and challenging issue in botany and image analysis.
This is because leaves of the same class exhibit very large differences, and leaves of …

Few-shot class-incremental learning was introduced to solve the model adaptation problem
for new incremental classes with only a few examples while still remaining effective for old …

In the field of intelligent multimedia analysis, ultra-fine-grained visual categorization (Ultra-
FGVC) plays a vital role in distinguishing intricate subcategories within broader categories …

Fine-grained leaf image retrieval (FGLIR) aims to search similar leaf images in subspecies
level which involves very high interclass visual similarity and accordingly poses great …

Highlights What are the main findings? LightGBM, among the selected black-box models,
was identified as requiring explanation due to its performance in solar power generation …

Content based image retrieval (CBIR) systems compare a query image with images in a
dataset to find similar images to a query image. In this paper a novel and efficient CBIR …

Fine-grained visual recognition is a highly challenging problem due to the subtle differences
among subcategories. In this paper, we focus on variety recognition, a more challenging fine …

Butterfly image retrieval is a challenging issue requiring the feature representation not only
to be sensitive to the subtle inter-class difference but also to remain robust to large intra …