Found 1508 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

Deep minimax probability machine

In order to alleviate this problem, we propose the Deep Minimax Probability Machine (DeepMPM), which applies MPM to deep neural networks in an end-to-end fashion. Expand abstract.
1 day ago
10/10 relevant
arXiv

Logic-inspired Deep Neural Networks

Deep neural networks have achieved impressive performance and become de-facto standard in many tasks. Expand abstract.
3 days ago
10/10 relevant
arXiv

Skin Lesion Classification Using Deep Neural Network

This paper reports the methods and techniques we have developed for classify dermoscopic images (task 1) of the ISIC 2019 challenge dataset for skin lesion classification, our approach aims to use ensemble deep neural network with some powerful techniques to deal with unbalance data sets as its the... Expand abstract.
4 days ago
8/10 relevant
arXiv

Unsupervised domain adaptation for the automated segmentation of neuroanatomy in MRI: a deep learning approach

Using a previously validated state-of-the-art segmentation method based on a context-augmented convolutional neural network, we first demonstrate that networks with better domain generalizability can be trained using extensive data augmentation with label-preserving transformations which mimic differences... Expand abstract.
7 days ago
5/10 relevant
bioRxiv

Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks

However, it is still unclear how the brain can perform credit assignment across many areas as efficiently as backpropagation does in deep neural networks. Expand abstract.
7 days ago
9/10 relevant
arXiv

There is Limited Correlation between Coverage and Robustness for Deep Neural Networks

Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. Expand abstract.
9 days ago
10/10 relevant
arXiv

Deep-Aligned Convolutional Neural Network for Skeleton-based Action Recognition and Segmentation

Convolutional neural networks (CNNs) are deep learning frameworks which are well-known for their notable performance in classification tasks. Expand abstract.
10 days ago
9/10 relevant
arXiv

Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks

In the semantic segmentation of street scenes, the reliability of a prediction is of highest interest. Expand abstract.
10 days ago
5/10 relevant
arXiv

Using Deep Neural Networks for Estimating Loop Unrolling Factor

In this paper, we address Loop unrolling optimization, by proposing a deep Neural Network model to predict the optimal unrolling factor for programs written for TIRAMISU. Expand abstract.
12 days ago
10/10 relevant
arXiv

Non-intrusive model reduction of large-scale, nonlinear dynamical systems using deep learning

This work develops a non-intrusive method to efficiently and accurately approximate the expensive nonlinear terms that arise in reduced nonlinear dynamical system using deep neural networks. Expand abstract.
13 days ago
8/10 relevant
arXiv