[PDF] Top 20 Adaptive Dictionary Learning For Competitive Classification Of Multiple Sclerosis Lesions
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Adaptive Dictionary Learning For Competitive Classification Of Multiple Sclerosis Lesions
... elements of an over-complete dictionary and have been used in many image processing ...an adaptive dictionary learning paradigm to automatically classify Multiple ... Voir le document complet
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Classification of Multiple Sclerosis Lesions using Adaptive Dictionary Learning
... ability of sparse representations to approximate high-dimensional images using a few representative signals in a low-dimensional subspace and the development of effi- cient sparse coding and ... Voir le document complet
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Detection of Multiple Sclerosis Lesions using Sparse Representations and Dictionary Learning
... versus lesions to help improve the ...detect multiple sclerosis lesions using dictionary ...performance of three methods which either use one dictionary, treating ... Voir le document complet
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Online Graph Dictionary Learning
... also competitive for ...models for clustering tasks with the following state-of-the-art OT models: i) GWF ( Xu , 2020 ), using the proximal point algorithm detailed in that paper and exploring ... Voir le document complet
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Multivariate Temporal Dictionary Learning for EEG
... Keywords: Dictionary learning, orthogonal matching pursuit, multivariate, shift-invariance, EEG, evoked potentials, ...potentials of large neuronal as- ...period of time between two ... Voir le document complet
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Dictionary Learning for Massive Matrix Factorization
... in classification) ceases to ...performance of the proposed algorithm on recommender systems for explicit feedback, a well-studied matrix completion ...scalability of our method on datasets ... Voir le document complet
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Dictionary learning for M/EEG multidimensional data
... I The method shows superior performance and less noisy estimated waveforms compared to the original single-channel JADL framework, both on synthetic and real data. I It is more robust to various levels of noise. I ... Voir le document complet
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Learning Multiple Markov Chains via Adaptive Allocation
... stream of research on Markov chains, which is more relevant to our work, investigates learning and estimation of the transition matrix (as opposed to its full law); see, ...investigates ... Voir le document complet
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Augmented dictionary learning for motion prediction
... Augmented Dictionary Learning for Motion Prediction Yu Fan Chen, Miao Liu, and Jonathan ...sentations of multivariate trajectories is important for under- standing the behavior patterns ... Voir le document complet
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Learning A Tree-Structured Dictionary For Efficient Image Representation With Adaptive Sparse Coding
... tree-structured dictionary for sparse representations, as well as a new adaptive sparse coding method, in a context of im- age ...Each dictionary at a level in the tree is learned from ... Voir le document complet
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Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals
... Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals Sebastian Hitziger1, Maureen Clerc1, Alexandre Gramfort2, Sandrine Saillet3, Christian Bénar3, Théodore ... Voir le document complet
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Jitter-Adaptive Dictionary Learning -Application to Multi-Trial Neuroelectric Signals
... entirety of the signals to provide global high-level ...common dictionary learning formulation as a matrix factorization problem, however, cannot compensate for the time delays ...possibly ... Voir le document complet
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αβ T-cell receptors from multiple sclerosis brain lesions show MAIT cell–related features
... contain lesions with high numbers of CD8 1 T ...sections of MS brain, the following antibodies against cell surface molecules were used: mouse anti-human CD161 (1:5, 191B8, Miltenyi Biotec, Bergisch ... Voir le document complet
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Learning brain alterations in multiple sclerosis from multimodal neuroimaging data
... deep learning techniques [ Sevetlidis, 2016 ; Xiang, 2018 ; Wang, 2018a ] have emerged as a powerful alternative and alleviate the above drawbacks for medical image ...synthesis. For instance, ... Voir le document complet
118
MSSEG Challenge Proceedings: Multiple Sclerosis Lesions Segmentation Challenge Using a Data Management and Processing Infrastructure
... mentation of multiple sclerosis lesions in a multi-stage ...avails of complementary information from multiple MR sequences, and includes additional estimated weight variables to ... Voir le document complet
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Decomposition and dictionary learning for 3D trajectories
... ability of the ...A dictionary Ψ of L = 45 normalized trivariate kernels is cre- ated from white uniform noise, and the kernels length is T = 18 ...composed of Q = 2000 signals of ... Voir le document complet
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A diffusion strategy for distributed dictionary learning
... sparsity of x n (i) means that only few components of x n (i) are non ...unique dictionary D gen- erates the observations at all ...this dictionary in a distributed manner thanks to in-network ... Voir le document complet
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Unsupervised Domain Adaptation With Optimal Transport in Multi-Site Segmentation of Multiple Sclerosis Lesions From MRI Data
... representative of all clinical scenarios, resulting in supervised models that suffer from poor generalization when applied to a new target image domain ( Commowick et ...Transfer Learning strategies ( ... Voir le document complet
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DOLPHIn - Dictionary Learning for Phase Retrieval
... Impact of Increased Inner Iteration Counts It is worth considering whether more inner ...steps for the different variable blocks— lead to further improvements of the results and / or faster ... Voir le document complet
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Classification of Multiple Sclerosis patients using a histogram-based K-Nearest Neighbors algorithm
... HAL Id: hal-02156448 https://hal-enac.archives-ouvertes.fr/hal-02156448 Submitted on 14 Jun 2019 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research ... Voir le document complet
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