Multimodal learning provides a path to fully utilize all types of information related to the
modeling target to provide the model with a global vision. Zero‐shot learning (ZSL) is a …

Breast cancer is a common malignancy and early detection and treatment of it is crucial.
Computer-aided diagnosis (CAD) based on deep learning has significantly advanced …

In generalized zero-shot classification, test samples can belong to either seen or unseen
classes. However, in real-world situations, there may be many open-set samples in the test …

Zero-shot learning aims to recognize objects from novel concepts through the model trained
on seen class data and assisted by the semantic descriptions. Though it breaks the serious …

Skin lesion is one of the most commonly encountered illnesses that need to be detected and
treated at an early stage. Numerous Convolutional Neural Network (CNN) classifiers were …

Abstract Zero-Shot Learning (ZSL) learns models for recognizing new classes. One of the
main challenges in ZSL is the domain discrepancy caused by the category inconsistency …

Zero-shot learning is a promising technique for diagnosing mechanical faults in complex
and uncertain environments. However, when diagnosing mechanical faults across different …

In recent years, unmanned aerial vehicles (UAVs) have experienced rapid development.
However, image recognition tasks from the UAV's viewpoint frequently encounter difficulties …

Zero-shot learning recognizes the unseen samples via the model learned from the seen
class samples and semantic features. Due to the lack of information of unseen class …

Abstract Generalized Zero-Shot Learning (GZSL) endeavors to recognize instances of seen
and unseen classes using semantic information and labeled instances of only seen classes …