Art Analysis
10 papers with code • 0 benchmarks • 2 datasets
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Latest papers with no code
PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy
As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microcopy.
Understanding and Creating Art with AI: Review and Outlook
Technologies related to artificial intelligence (AI) have a strong impact on the changes of research and creative practices in visual arts.
Feature reduction for machine learning on molecular features: The GeneScore
We present the GeneScore, a concept of feature reduction for Machine Learning analysis of biomedical data.
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars
Past methods for inferring color in underdrawings have been based on physical x-ray fluorescence spectral imaging of pigments in ghost-paintings and are thus expensive, time consuming, and require equipment not available in most conservation studios.
An analysis of the transfer learning of convolutional neural networks for artistic images
Transfer learning from huge natural image datasets, fine-tuning of deep neural networks and the use of the corresponding pre-trained networks have become de facto the core of art analysis applications.
Shared Space Transfer Learning for analyzing multi-site fMRI data
The optimization procedure extracts the common features for each site by using a single-iteration algorithm and maps these site-specific common features to the site-independent shared space.
Demographic Influences on Contemporary Art with Unsupervised Style Embeddings
Art produced today, on the other hand, is numerous and easily accessible, through the internet and social networks that are used by professional and amateur artists alike to display their work.
Anomalous subdiffusion in living cells: bridging the gap between experiments and realistic models through collaborative challenges
Among them, fluorescence correlation spectroscopy (FCS) and single-particle tracking (SPT) have proven to be instrumental to our understanding of cell dynamics and function.
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
We show that the gradient norm $\|\nabla f(x)\|$ for $x \sim \exp(-f(x))$, where $f$ is strongly convex and smooth, concentrates tightly around its mean.
Adaptive Direction-Guided Structure Tensor Total Variation
Direction-guided structure tensor total variation (DSTV) is a recently proposed regularization term that aims at increasing the sensitivity of the structure tensor total variation (STV) to the changes towards a predetermined direction.
