Face recognition: Past, present and future (a review)
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 …
behavioral characteristics of an individual. The main feature of biometric systems is the use …
Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review
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 …
sparse representation (SR) has attracted significant attention in multi-sensor image fusion …
Image super-resolution with non-local sparse attention
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 …
Resolution (SISR). In this paper, we investigate their combinations and propose a novel Non …
A survey on deep learning for data-driven soft sensors
Q Sun, Z Ge - IEEE Transactions on Industrial Informatics, 2021 - ieeexplore.ieee.org
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 …
prediction, and many other important applications. With the development of hardware and …
Infrared and visible image fusion methods and applications: A survey
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 …
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …
Learning vector-quantized item representation for transferable sequential recommenders
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 …
recommender systems. The basic idea is to employ pre-trained language models (PLM) to …
An efficient specific emitter identification method based on complex-valued neural networks and network compression
Specific emitter identification (SEI) is a promising technology to discriminate the individual
emitter and enhance the security of various wireless communication systems. SEI is …
emitter and enhance the security of various wireless communication systems. SEI is …
Breast cancer classification from histopathological images using patch-based deep learning modeling
Accurate detection and classification of breast cancer is a critical task in medical imaging
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …
Tensor methods in computer vision and deep learning
Tensors, or multidimensional arrays, are data structures that can naturally represent visual
data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic …
data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic …
Vitmatte: Boosting image matting with pre-trained plain vision transformers
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 …
information by predicting alpha matte for each pixel. Recently, plain vision Transformers …