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Image Style Transfer Using Convolutional Neural Networks
TLDR
A Neural Algorithm of Artistic Style is introduced that can separate and recombine the image content and style of natural images and provide new insights into the deep image representations learned by Convolutional Neural Networks and demonstrate their potential for high level image synthesis and manipulation. Expand
A Neural Algorithm of Artistic Style
TLDR
This work introduces an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality and offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery. Expand
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
TLDR
It is shown that ImageNet-trained CNNs are strongly biased towards recognising textures rather than shapes, which is in stark contrast to human behavioural evidence and reveals fundamentally different classification strategies. Expand
DeepLabCut: markerless pose estimation of user-defined body parts with deep learning
TLDR
Using a deep learning approach to track user-defined body parts during various behaviors across multiple species, the authors show that their toolbox, called DeepLabCut, can achieve human accuracy with only a few hundred frames of training data. Expand
Texture Synthesis Using Convolutional Neural Networks
TLDR
A new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition is introduced, showing that across layers the texture representations increasingly capture the statistical properties of natural images while making object information more and more explicit. Expand
Decorrelated Neuronal Firing in Cortical Microcircuits
TLDR
The findings suggest a refinement of current models of cortical microcircuit architecture and function: Either adjacent neurons share only a few percent of their inputs or, alternatively, their activity is actively decorrelated. Expand
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
TLDR
The Boundary Attack is introduced, a decision-based attack that starts from a large adversarial perturbations and then seeks to reduce the perturbation while staying adversarial and is competitive with the best gradient-based attacks in standard computer vision tasks like ImageNet. Expand
A note on the evaluation of generative models
TLDR
This article reviews mostly known but often underappreciated properties relating to the evaluation and interpretation of generative models with a focus on image models and shows that three of the currently most commonly used criteria---average log-likelihood, Parzen window estimates, and visual fidelity of samples---are largely independent of each other when the data is high-dimensional. Expand
The functional diversity of retinal ganglion cells in the mouse
TLDR
It is shown that the mouse retina harbours substantially more than 30 functional output channels, which include all known and several new ganglion cell types, as verified by genetic and anatomical criteria. Expand
State Dependence of Noise Correlations in Macaque Primary Visual Cortex
TLDR
This work found that under opioid anesthesia, activity was dominated by strong coordinated fluctuations on a timescale of 1-2 Hz, which were mostly absent in awake, fixating monkeys, which markedly reduced correlations under anesthesia, matching those observed during wakefulness and reconciling earlier studies conducted under anesthesia and in awake animals. Expand
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