[HTML][HTML] Deep learning in multimedia healthcare applications: a review
The increase in chronic diseases has affected the countries' health system and economy.
With the recent COVID-19 virus, humanity has experienced a great challenge, which has led …
With the recent COVID-19 virus, humanity has experienced a great challenge, which has led …
The new generation brain-inspired sparse learning: A comprehensive survey
In recent years, the enormous demand for computing resources resulting from massive data
and complex network models has become the limitation of deep learning. In the large-scale …
and complex network models has become the limitation of deep learning. In the large-scale …
Convolution enabled transformer via random contrastive regularization for rotating machinery diagnosis under time-varying working conditions
Mechanical equipment such as wind turbines often operates under time-varying working
conditions (TVWC). The vibration signals collected from their key rotating components, such …
conditions (TVWC). The vibration signals collected from their key rotating components, such …
Light transport induced domain adaptation for semantic segmentation in thermal infrared urban scenes
Semantic segmentation in urban scenes is widely used in applications of intelligent
transportation systems (ITS). In urban scenes, thermal infrared (TIR) images can be captured …
transportation systems (ITS). In urban scenes, thermal infrared (TIR) images can be captured …
[HTML][HTML] Hyperspectral image classification via deep structure dictionary learning
The construction of diverse dictionaries for sparse representation of hyperspectral image
(HSI) classification has been a hot topic over the past few years. However, compared with …
(HSI) classification has been a hot topic over the past few years. However, compared with …
Support vector machine embedding discriminative dictionary pair learning for pattern classification
J Dong, L Yang, C Liu, W Cheng, W Wang - Neural networks, 2022 - Elsevier
Discriminative dictionary learning (DDL) aims to address pattern classification problems via
learning dictionaries from training samples. Dictionary pair learning (DPL) based DDL has …
learning dictionaries from training samples. Dictionary pair learning (DPL) based DDL has …
GJTD-LR: A trainable grouped joint tensor dictionary with low-rank prior for single hyperspectral image super-resolution
Reconstructing a high-resolution hyperspectral image (HR-HSI) using a single low-
resolution hyperspectral image (LR-HSI) is a significant technique for increasing the spatial …
resolution hyperspectral image (LR-HSI) is a significant technique for increasing the spatial …
Fault diagnosis of complex industrial systems based on multi-granularity dictionary learning and its application
Nowadays, the intelligent fault diagnosis problem of modern industrial systems has received
increasing attention. However, with the increasing scale of industrial systems, the same …
increasing attention. However, with the increasing scale of industrial systems, the same …
Self-balancing dictionary learning for relaxed collaborative representation of hyperspectral image classification
Supervised dictionary learning and representation (S-DLR) learning framework has
demonstrated its superiority for hyperspectral image classification. Relaxed collaborative …
demonstrated its superiority for hyperspectral image classification. Relaxed collaborative …
Multi-feature sparse similar representation for person identification
Person identification with a single feature (eg, face recognition, speaker verification, person
re-identification, etc.) has been studied extensively for many years, while few works focus on …
re-identification, etc.) has been studied extensively for many years, while few works focus on …