Small data challenges for intelligent prognostics and health management: a review
Prognostics and health management (PHM) is critical for enhancing equipment reliability
and reducing maintenance costs, and research on intelligent PHM has made significant …
and reducing maintenance costs, and research on intelligent PHM has made significant …
Learning adversarial semantic embeddings for zero-shot recognition in open worlds
Abstract Zero-Shot Learning (ZSL) focuses on classifying samples of unseen classes with
only their side semantic information presented during training. It cannot handle real-life …
only their side semantic information presented during training. It cannot handle real-life …
A novel mechanical fault diagnosis for high-voltage circuit breakers with zero-shot learning
Q Yang, Y Liao - Expert Systems with Applications, 2024 - Elsevier
In recent years, data-driven methods have been widely used in the field of high-voltage
circuit breakers (HVCBs) fault diagnosis. However, due to the complex mechanical structure …
circuit breakers (HVCBs) fault diagnosis. However, due to the complex mechanical structure …
A Multi-Group Multi-Stream attribute Attention network for fine-grained zero-shot learning
Fine-grained visual categorization in zero-shot setting is a challenging problem in the
computer vision community. It requires algorithms to accurately identify fine-grained …
computer vision community. It requires algorithms to accurately identify fine-grained …
Open-Pose 3D zero-shot learning: Benchmark and challenges
With the explosive 3D data growth, the urgency of utilizing zero-shot learning to facilitate
data labeling becomes evident. Recently, methods transferring language or language …
data labeling becomes evident. Recently, methods transferring language or language …
TransRefine: Transformer-augmented feature refinement for zero-shot scene classification in remote sensing images
R Damalla, PA Bendre, C Gayathri, R Datla… - Pattern Recognition, 2025 - Elsevier
Zero-shot learning becomes challenging in classifying scenes of unseen classes due to the
typical characteristics of remote-sensing images. The intricate variations among the scenes …
typical characteristics of remote-sensing images. The intricate variations among the scenes …
Cross-modal knowledge transfer for 3D point clouds via graph offset prediction
A Point cloud is an important representation of three-dimensional (3D) objects, playing an
important role in computer vision. However, the inherent sparseness and disorder of point …
important role in computer vision. However, the inherent sparseness and disorder of point …
Transductive zero-shot learning with generative model-driven structure alignment
Zero-shot learning (ZSL) facilitates the transfer of knowledge from seen to unseen
categories through high-dimensional vectors that capture both known and unknown class …
categories through high-dimensional vectors that capture both known and unknown class …
Dynamic VAEs via semantic-aligned matching for continual zero-shot learning
Abstract Continual Zero-shot Learning (CZSL) is capable of classifying unseen categories
across a sequence of tasks. However, CZSL is often plagued by the challenge of …
across a sequence of tasks. However, CZSL is often plagued by the challenge of …
Linear centroid encoder for supervised principal component analysis
We propose a new supervised dimensionality reduction technique called Supervised Linear
Centroid-Encoder (SLCE), a linear counterpart of the nonlinear Centroid-Encoder …
Centroid-Encoder (SLCE), a linear counterpart of the nonlinear Centroid-Encoder …