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Found 6 papers, 2 papers with code
LSTM-CNN: An efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysis
Conclusions: We present a series of experiments with extensive analysis, which systematically demonstrate the effectiveness and efficiency of the proposed hybrid neural network in extracting distinctive handwriting patterns for precise diagnosis of Parkinson's disease.
Optimal Image Transport on Sparse Dictionaries
In this paper, we derive a novel optimal image transport algorithm over sparse dictionaries by taking advantage of Sparse Representation (SR) and Optimal Transport (OT).
Semi-sparsity Priors for Image Structure Analysis and Extraction
Image structure-texture decomposition is a long-standing and fundamental problem in both image processing and computer vision fields.
A Light-weight CNN Model for Efficient Parkinson's Disease Diagnostics
In recent years, deep learning methods have achieved great success in various fields due to their strong performance in practical applications.
Intrinsic Image Transfer for Illumination Manipulation
We illustrate that all losses can be reduced without the necessity of taking an intrinsic image decomposition under the well-known spatial-varying illumination illumination-invariant reflectance prior knowledge.
Semi-Sparsity for Smoothing Filters
In this paper, we propose an interesting semi-sparsity smoothing algorithm based on a novel sparsity-inducing optimization framework.
