Disaggregating Transform Learning for Non-Intrusive Load Monitoring
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2850707
Abstract: This paper addresses the problem of energy disaggregation/non-intrusive load monitoring. It introduces a new method based on the transform learning formulation. Several recent techniques, such as discriminative sparse coding, powerlet disaggregation, and deep sparse coding,… read more here.
Keywords: load monitoring; sparse; sparse coding; non intrusive ... See more keywords
Accelerated Log-Regularized Convolutional Transform Learning and its Convergence Guarantee.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2021.3067352
Abstract: Convolutional transform learning (CTL), learning filters by minimizing the data fidelity loss function in an unsupervised way, is becoming very pervasive, resulting from keeping the best of both worlds: the benefit of unsupervised learning and… read more here.
Keywords: log; transform learning; convergence; convolutional transform ... See more keywords
Exploring Nonlocal Group Sparsity Under Transform Learning for Hyperspectral Image Denoising
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3202359
Abstract: Hyperspectral image (HSI) denoising has been regarded as an effective and economical preprocessing step in data subsequent applications. Recent nonlocal low-rank approximation on each full band patch group has demonstrated their superiority for HSI denoising.… read more here.
Keywords: hsi; nonlocal group; transform learning; image ... See more keywords
VIDOSAT: High-Dimensional Sparsifying Transform Learning for Online Video Denoising
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2018.2865684
Abstract: Techniques exploiting the sparsity of images in a transform domain are effective for various applications in image and video processing. In particular, transform learning methods involve cheap computations and have been demonstrated to perform well… read more here.
Keywords: video; video denoising; transform learning; online video ... See more keywords