Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

As a result of several successful applications in computer vision and image processing,
sparse representation (SR) has attracted significant attention in multi-sensor image fusion …

Both non-local (NL) operation and sparse representation are crucial for Single Image Super-
Resolution (SISR). In this paper, we investigate their combinations and propose a novel Non …

Recently, the generality of natural language text has been leveraged to develop transferable
recommender systems. The basic idea is to employ pre-trained language models (PLM) to …

Soft sensors are widely constructed in process industry to realize process monitoring, quality
prediction, and many other important applications. With the development of hardware and …

Image matting is an inverse fusion process that separates the foreground and background
information by predicting alpha matte for each pixel. Recently, plain vision Transformers …

Specific emitter identification (SEI) is a promising technology to discriminate the individual
emitter and enhance the security of various wireless communication systems. SEI is …

Infrared images can distinguish targets from their backgrounds based on the radiation
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …

Due to the rapid development of multimedia technology and sensor technology, multi-view
clustering (MVC) has become a research hotspot in machine learning, data mining, and …

Tensors, or multidimensional arrays, are data structures that can naturally represent visual
data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic …