Human-centric assembly is emerging as a promising paradigm for achieving mass
personalization in the context of Industry 5.0, as it fully capitalizes on the advantages of …

In the field of fine-grained visual recognition (FGVR), the ability to resolve minute and often
subtle differences between highly similar object categories is paramount. The advent of …

Fine-grained visual classification (FGVC) aims to identify objects belonging to multiple sub-
categories of the same super-category. The key to solving fine-grained classification …

Fine-grained object recognition (FGOR) aims to learn discriminative features that can
identify the subtle distinctions between visually similar objects. However, less effort has …

Crop yield production could be enhanced for agricultural growth if various plant nutrition
deficiencies, and diseases are identified and detected at early stages. Hence, continuous …

Fine-grained visual classification is a challenging task due to the high similarity between
categories and distinct differences among data within one single category. To address the …

Human body-pose estimation is a complex problem in computer vision. Recent research
interests have been widened specifically on the sports, yoga, and dance (SYD) postures for …

The yield of rice crops is strongly correlated to the number of panicles per unit area.
Computer vision techniques have been utilized in previous studies to count the number of …

CLIP-based classifiers rely on the prompt containing a {class name} that is known to the text
encoder. Therefore, they perform poorly on new classes or the classes whose names rarely …

Sequential Recommendation is a widely studied paradigm for learning users' dynamic
interests from historical interactions for predicting the next potential item. Although lots of …