Fringe projection is widely recognized as a prominent technique for 3D measurement, owing
to its non-contact nature, high precision, and exceptional spatial resolution. However, it …

Wind turbines play a crucial role in renewable energy generation systems and are frequently
exposed to challenging operational environments. Monitoring and diagnosing potential …

Semi-supervised clustering is a new learning method which combines semi-supervised
learning (SSL) and cluster analysis. It is widely valued and applied to machine learning …

Recent developments in multimodal training methodologies, including CLIP and ALIGN,
obviate the necessity for individual data labeling. These approaches utilize pairs of data and …

The click feature of an image, defined as the user click frequency vector of the image on a
predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained …

Recently, multi-view representation learning has become a rapidly growing direction in
machine learning and data mining areas. This paper introduces two categories for multi …

Most existing approaches address multi-view subspace clustering problem by constructing
the affinity matrix on each view separately and afterwards propose how to extend spectral …

Hyperspectral image (HSI) consists of hundreds of continuous narrowbands with high
spectral correlation, which would lead to the so-called Hughes phenomenon and the high …

Recently, image captioning has achieved great progress in computer vision and artificial
intelligence. However, language models still failed to achieve the desired results in high …

Density based clustering methods are proposed for clustering spatial databases with noise.
Density Based Spatial Clustering of Applications with Noise (DBSCAN) can discover …