Distribution service restoration with renewable energy sources: a review
AH Alobaidi, SS Fazlhashemi… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Distribution service restoration plays a vital role in mitigating the adverse impacts of power
outages stemming from extreme weather conditions. With incentives toward reducing the …
outages stemming from extreme weather conditions. With incentives toward reducing the …
Discriminative fisher embedding dictionary learning algorithm for object recognition
Both interclass variances and intraclass similarities are crucial for improving the
classification performance of discriminative dictionary learning (DDL) algorithms. However …
classification performance of discriminative dictionary learning (DDL) algorithms. However …
When dictionary learning meets deep learning: Deep dictionary learning and coding network for image recognition with limited data
We present a new deep dictionary learning and coding network (DDLCN) for image-
recognition tasks with limited data. The proposed DDLCN has most of the standard deep …
recognition tasks with limited data. The proposed DDLCN has most of the standard deep …
Spatiotemporal behind-the-meter load and PV power forecasting via deep graph dictionary learning
In recent years, with the rapid growth of rooftop photovoltaic (PV) generation in distribution
networks, power system operators call for accurate forecasts of the behind-the-meter (BTM) …
networks, power system operators call for accurate forecasts of the behind-the-meter (BTM) …
Discriminative local sparse representation by robust adaptive dictionary pair learning
In this article, we propose a structured robust adaptive dictionary pair learning (RA-DPL)
framework for the discriminative sparse representation (SR) learning. To achieve powerful …
framework for the discriminative sparse representation (SR) learning. To achieve powerful …
Multi-resolution dictionary learning for face recognition
In recent years, there has been a growing interest in the study of dictionary learning for face
recognition. Most of the conventional dictionary learning methods focus only on a single …
recognition. Most of the conventional dictionary learning methods focus only on a single …
A novel dimension reduction and dictionary learning framework for high-dimensional data classification
Y Li, Y Chai, H Zhou, H Yin - Pattern Recognition, 2021 - Elsevier
High-dimensional problem poses significant challenges for dictionary learning based
classification architecture. Joint Dimension Reduction and Dictionary Learning (JDRDL) …
classification architecture. Joint Dimension Reduction and Dictionary Learning (JDRDL) …
A hierarchical discriminative sparse representation classifier for EEG signal detection
X Gu, C Zhang, T Ni - IEEE/ACM transactions on computational …, 2020 - ieeexplore.ieee.org
Classification of electroencephalogram (EEG) signal data plays a vital role in epilepsy
detection. Recently sparse representation-based classification (SRC) methods have …
detection. Recently sparse representation-based classification (SRC) methods have …
Chunk incremental learning for cost-sensitive hinge loss support vector machine
Cost-sensitive learning can be found in many real-world applications and represents an
important learning paradigm in machine learning. The recently proposed cost-sensitive …
important learning paradigm in machine learning. The recently proposed cost-sensitive …
Streamer action recognition in live video with spatial-temporal attention and deep dictionary learning
C Li, J Zhang, J Yao - Neurocomputing, 2021 - Elsevier
Live video hosted by streamer is being sought after by more and more Internet users. A few
streamers show inappropriate action in normal live video content for profit and popularity …
streamers show inappropriate action in normal live video content for profit and popularity …