Suchergebnisse - Non-negative sparse coding

An Entorhinal-Hippocampal Loop Model Based on Non-negative Sparse Coding

Autoren: Kaixin Zhao Menghui Ren

Quelle: Journal of The Institution of Engineers (India): Series B. 106:113-127

From Convolutional Sparse Coding To *-NMF Factorization of Time-Frequency Coefficients

Autoren: Malagnoux, Jean-Baptiste Kowalski, Matthieu

Weitere Verfasser: Malagnoux, Jean-Baptiste Kowalski, Matthieu

Quelle: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :5530-5534

Schlagwörter: Convolutional Dictionary Learning, Convolutional Sparse Coding, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Time-Frequency synthesis, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], Non-negative Matrix Factorization

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.science/hal-04608586v1/document
https://hal.science/hal-04608586v1
https://doi.org/10.1109/icassp48485.2024.10447466

Incorporation of Histogram Intersection and Semantic Information into Non-Negative Local Laplacian Sparse Coding for Image Classification

Autoren: Ying Shi Yuan Wan Xinjian Wang et al.

Quelle: Mathematics, Vol 13, Iss 2, p 219 (2025)

Schlagwörter: semantic information, sparse coding, QA1-939, support vector machine, image representation, Mathematics, image classification

Zugangs-URL: https://doaj.org/article/eb68a77f35264b02a29a1b1ba25cb76a

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms

Autoren: Xie, Jianwen Douglas, Pamela K Wu, Ying Nian et al.

Quelle: Journal of Neuroscience Methods. 282

Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 3209 Neurosciences (for-2020), Clinical Research (rcdc), Machine Learning and Artificial Intelligence (rcdc), Neurosciences (rcdc), Biomedical Imaging (rcdc), Bioengineering (rcdc), Algorithms (mesh), Auditory Perception (mesh), Brain (mesh), Brain Mapping (mesh), Cerebrovascular Circulation (mesh), Humans (mesh), Magnetic Resonance Imaging (mesh), Motion Perception (mesh), Neural Pathways (mesh), Neuropsychological Tests (mesh), Oxygen (mesh), Rest (mesh), FMRI, Classification, ICA, NMF, K-SVD, L1 Regularized Learning, Independent component analysis, Brain (mesh), Neural Pathways (mesh), Humans (mesh), Oxygen (mesh), Magnetic Resonance Imaging (mesh), Brain Mapping (mesh), Auditory Perception (mesh), Motion Perception (mesh), Neuropsychological Tests (mesh), Cerebrovascular Circulation (mesh), Algorithms (mesh), Rest (mesh), Artifacts, Classification, FMRI, ICA, Image processing, Independent component analysis, K-SVD, L1 Regularized Learning, Machine learning, NMF, Negative BOLD signal, Non-negative matrix factorization, Pattern recognition, Random forests, Sparsity, Support vector machines, Algorithms (mesh), Auditory Perception (mesh), Brain (mesh), Brain Mapping (mesh), Cerebrovascular Circulation (mesh), Humans (mesh), Magnetic Resonance Imaging (mesh), Motion Perception (mesh), Neural Pathways (mesh), Neuropsychological Tests (mesh), Oxygen (mesh), Rest (mesh), 1109 Neurosciences (for), 1701 Psychology (for), 1702 Cognitive Sciences (for), Neurology & Neurosurgery (science-metrix), 3209 Neurosciences (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/2n032848
https://escholarship.org/content/qt2n032848/qt2n032848.pdf

Heterogeneous convolutive non-negative sparse coding

Autoren: Wang, Dong Tejedor Noguerales, Javier UAM. Departamento de Tecnología Electrónica y de las Comunicaciones et al.

Weitere Verfasser: Wang, Dong Tejedor Noguerales, Javier UAM. Departamento de Tecnología Electrónica y de las Comunicaciones et al.

Quelle: Biblos-e Archivo. Repositorio Institucional de la UAM
instname
Universidad Autónoma de Madrid

Schlagwörter: Informática, Telecomunicaciones, Sparse coding, Speech processing, Non-negative matrix factorization

Dateibeschreibung: application/pdf

Zugangs-URL: https://repositorio.uam.es/bitstream/10486/666457/3/heterogeneus_wang_Interspeech_2012.pdf
http://hdl.handle.net/10486/666457

A diagonalized newton algorithm for non-negative sparse coding

Autoren: Van hamme, Hugo

Quelle: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. :7299-7303

Schlagwörter: Technology, Science & Technology, sparse coding, Engineering, Electrical & Electronic, PSI_SPEECH, Acoustics, vocabulary acquisition, 02 engineering and technology, Kullback Leibler divergence, non-negative matrix factorization, Engineering, Newton method, source separation, MATRIX FACTORIZATION, 0202 electrical engineering, electronic engineering, information engineering

Zugangs-URL: https://dblp.uni-trier.de/db/conf/icassp/icassp2013.html#hamme13
http://www.esat.kuleuven.be/psi/spraak/cgi-bin/get_file.cgi?/hvanhamm/icassp13/DNAv09.pdf&auto&hvh:ICASSP13
https://lirias.kuleuven.be/handle/123456789/396301
https://doi.org/10.1109/icassp.2013.6639080

Non-negative and local sparse coding based on l2-norm and Hessian regularization

Autoren: Jinghui Zhang Yuan Wan Zhiping Chen et al.

Quelle: Information Sciences. 486:88-100

Schlagwörter: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://www.sciencedirect.com/science/article/pii/S0020025519301343
https://doi.org/10.1016/j.ins.2019.02.024
https://dblp.uni-trier.de/db/journals/isci/isci486.html#ZhangWCM19

An Entorhinal-Hippocampal Loop Model Based on Non-negative Sparse Coding.

Autoren: Zhao, Kaixin Ren, Menghui

Quelle: Journal of the Institution of Engineers (India): Series B. Feb2025, Vol. 106 Issue 1, p113-127. 15p.

Modelling object recognition in visual cortex using multiple firing K-means and non-negative sparse coding

Autoren: Limiao Deng

Quelle: Cognitive and Neural Modelling for Visual Information Representation and Memorization ISBN: 9781003281641

Facial Expression Recognition via Non-Negative Least-Squares Sparse Coding

Autoren: Ying Chen Xiaoming Zhao Shiqing Zhang

Quelle: Information, Vol 5, Iss 2, Pp 305-318 (2014)
Information; Volume 5; Issue 2; Pages: 305-318

Schlagwörter: non-negative least-squares, sparse coding, local binary patterns, facial expression recognition, 0202 electrical engineering, electronic engineering, information engineering, Information technology, 02 engineering and technology, T58.5-58.64

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.mdpi.com/2078-2489/5/2/305/pdf
https://doaj.org/article/200d9f8668fe442794b1148d28abf95c
https://dblp.uni-trier.de/db/journals/information/information5.html#ChenZZ14
https://doi.org/10.3390/info5020305
https://www.mdpi.com/2078-2489/5/2/305/pdf
https://www.mdpi.com/2078-2489/5/2/305/htm
http://core.ac.uk/display/27087305

Grey Level Co-Occurrence Matrix (GLCM) and Multi-Scale Non-Negative Sparse Coding For Classification of Medical Images

Autoren: Dr.G. Satyavathy P. Dhanalakshmi

Quelle: Journal of Advanced Research in Dynamical and Control Systems. 11:481-493

Schlagwörter: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://www.jardcs.org/abstract.php?id=2684

Robust Non-negative Block Sparse Coding for Acoustic Novelty Detection

Autoren: Karim Helwani Ritwik Giri Arvindh Krishnaswamy

Quelle: Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019). :74-78

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: http://archive.nyu.edu/bitstream/2451/60731/1/DCASE2019Workshop_Giri_84.pdf
https://assets.amazon.science/c2/ca/eabaea814b279bd13851dba120dc/robust-non-negative-block-sparse-coding-for-acoustic-novelty.pdf
https://archive.nyu.edu/bitstream/2451/60731/1/DCASE2019Workshop_Giri_84.pdf
https://www.amazon.science/publications/robust-non-negative-block-sparse-coding-for-acoustic-novelty-detection

Learning an efficient hippocampal place map from entorhinal inputs using non-negative sparse coding

Autoren: Lian, Y Burkitt, AN

Index Begriffe: Journal Article

URL: https://hdl.handle.net/11343/281230

Combining Non-negative Matrix Factorization and Sparse Coding for Functional Brain Overlapping Community Detection

Autoren: Zilan Hu Xuan Li Haixian Wang

Quelle: Cognitive Computation. 10:991-1005

Schlagwörter: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, 3. Good health

Zugangs-URL: https://dblp.uni-trier.de/db/journals/cogcom/cogcom10.html#LiHW18
https://link.springer.com/article/10.1007%2Fs12559-018-9585-6

Non-negative Local Sparse Coding for Subspace Clustering

Autoren: Hosseini, Babak Hammer, Barbara Duivesteijn, Wouter et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783030017675

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Subspace Clustering, Sparse Coding, Machine Learning (stat.ML), 02 engineering and technology, Machine Learning (cs.LG), Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Statistics - Machine Learning, Computer Science - Data Structures and Algorithms, 0202 electrical engineering, electronic engineering, information engineering, Data Mining, Data Structures and Algorithms (cs.DS)

Dateibeschreibung: application/vnd.openxmlformats-officedocument.presentationml.presentation

Zugangs-URL: http://arxiv.org/pdf/1903.05239
http://arxiv.org/abs/1903.05239
https://rd.springer.com/chapter/10.1007/978-3-030-01768-2_12
https://pub.uni-bielefeld.de/download/2921209/2931846/IDA2018_last.pptx
https://doi.org/10.1007/978-3-030-01768-2_12
https://pub.uni-bielefeld.de/record/2921209
http://dblp.uni-trier.de/db/journals/corr/corr1903.html#abs-1903-05239
https://dblp.uni-trier.de/db/journals/corr/corr1903.html#abs-1903-05239
https://arxiv.org/pdf/1903.05239
http://ui.adsabs.harvard.edu/abs/2019arXiv190305239H/abstract
https://arxiv.org/abs/1903.05239
https://pub.uni-bielefeld.de/record/2921209

Medical image classification based on multi-scale non-negative sparse coding

Autoren: Jian Shen Arun Kumar Sangaiah Ruijie Zhang et al.

Quelle: Artificial Intelligence in Medicine. 83:44-51

Schlagwörter: Diagnostic Imaging, ROC Curve, Artificial Intelligence, Predictive Value of Tests, Image Interpretation, Computer-Assisted, 0202 electrical engineering, electronic engineering, information engineering, Humans, 02 engineering and technology, Pattern Recognition, Automated

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/28559133
https://dblp.uni-trier.de/db/journals/artmed/artmed83.html#ZhangSWLS17
https://www.sciencedirect.com/science/article/pii/S0933365716306029
https://dl.acm.org/doi/10.1016/j.artmed.2017.05.006
https://www.ncbi.nlm.nih.gov/pubmed/28559133
http://www.ncbi.nlm.nih.gov/pubmed/28559133
https://doi.org/10.1016/j.artmed.2017.05.006

Biomedical time series clustering based on non-negative sparse coding and probabilistic topic model

Autoren: Wang, J. Liu, P. F. H. She, M. et al.

Weitere Verfasser: Wang, J. Liu, P. F. H. She, M. et al.

Quelle: Computer Methods and Programs in Biomedicine. 111:629-641

Schlagwörter: Models, Statistical, sparse coding, probabilistic topic model, Electroencephalography, 02 engineering and technology, Signal-To-Noise Ratio, unsupervised learning, Electrocardiography, 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Cluster Analysis, Humans, bag-of-words, Probability

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/23846155
https://www.ncbi.nlm.nih.gov/pubmed/23846155
https://dblp.uni-trier.de/db/journals/cmpb/cmpb111.html#WangLSNK13
https://doi.org/10.1016/j.cmpb.2013.05.022
https://core.ac.uk/display/16422891
http://dro.deakin.edu.au/view/DU:30055372
https://www.sciencedirect.com/science/article/pii/S016926071300179X
https://acuresearchbank.acu.edu.au/item/87v2q/biomedical-time-series-clustering-based-on-non-negative-sparse-coding-and-probabilistic-topic-model

Wearable Hearing Device Spectral Enhancement Driven by Non-Negative Sparse Coding-Based Residual Noise Reduction

Autoren: Seon Man Kim

Quelle: Sensors, Vol 20, Iss 20, p 5751 (2020)

Schlagwörter: hearing device, hearing aid, speech enhancement, Wiener filter, residual noise, non-negative sparse coding, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1424-8220/20/20/5751; https://doaj.org/toc/1424-8220

Zugangs-URL: https://doaj.org/article/c881c73b7a4e461e92db7a0eb4042950

Non-negative matrix factorisation incorporating greedy Hellinger sparse coding applied to polyphonic music transcription

Autoren: O'Hanlon, K Plumbley, MD Sandler, M

Quelle: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :2214-2218

Schlagwörter: 03 medical and health sciences, 06 humanities and the arts, 0305 other medical science, 0604 arts

Dateibeschreibung: text

Zugangs-URL: https://surrey-researchmanagement.esploro.exlibrisgroup.com/view/delivery/44SUR_INST/12139983540002346/13140370760002346
https://ieeexplore.ieee.org/document/7178364/
https://qmro.qmul.ac.uk/xmlui/handle/123456789/23409
https://dblp.uni-trier.de/db/conf/icassp/icassp2015.html#OHanlonSP15
http://dblp.uni-trier.de/db/conf/icassp/icassp2015.html#OHanlonSP15
https://surrey.eprints-hosting.org/807550/

Non negative matrix factorization, sparse coding & dictionary learning techniques on fMRI images

Autoren: Imran Ahmad Qureshi Syed M. Zubair Khurram Khurshid

Quelle: 2017 International Symposium on Recent Advances in Electrical Engineering (RAEE). :1-6

Schlagwörter: 03 medical and health sciences, 0302 clinical medicine

Zugangs-URL: https://ieeexplore.ieee.org/document/8246037/