Found 15510 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data

In many applications, one works with deep neural network (DNN) models trained by someone else. Expand abstract.
8 days ago
6/10 relevant
arXiv

ArcText: An Unified Text Approach to Describing Convolutional Neural Network Architectures

Numerous Convolutional Neural Network (CNN) models have demonstrated their promising performance mostly in computer vision. Expand abstract.
8 days ago
5/10 relevant
arXiv

Proteogenomic heterogeneity of localized human prostate cancer progression

Overall, this study revealed molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions. Expand abstract.
9 days ago
6/10 relevant
bioRxiv

Autonomous Unknown-Application Filtering and Labeling for DL-based Traffic Classifier Update

Specifically, Deep Learning (DL) has attracted much attention from the researchers due to its effectiveness even in encrypted network traffic without compromising neither user privacy nor network security. Expand abstract.
9 days ago
4/10 relevant
arXiv

Video Face Super-Resolution with Motion-Adaptive Feedback Cell

Video super-resolution (VSR) methods have recently achieved a remarkable success due to the development of deep convolutional neural networks (CNN). Expand abstract.
9 days ago
6/10 relevant
arXiv

Handover Probability in Drone Cellular Networks

For the SSM, we compute the exact handover probability by establishing equivalence with a single-tier terrestrial cellular network, in which the base stations (BSs) are static while the UEs are mobile. Expand abstract.
9 days ago
5/10 relevant
arXiv

Blind Adversarial Network Perturbations

However, deep neural networks are known to be vulnerable to adversarial examples: adversarial inputs to the model that get labeled incorrectly by the model due to small adversarial perturbations. Expand abstract.
9 days ago
7/10 relevant
arXiv

A closer look at the approximation capabilities of neural networks

The universal approximation theorem, in one of its most general versions, says that if we consider only continuous activation functions $\sigma$, then a standard feedforward neural network with one hidden layer is able to approximate any continuous multivariate function $f$ to any given approximation threshold $\varepsilon$, if and only if $\sigma$... Expand abstract.
9 days ago
9/10 relevant
arXiv

Coordinated Passive Beamforming for Distributed Intelligent Reflecting Surfaces Network

However, current works mainly focus on single IRS-empowered wireless networks, where the channel rank deficiency problem has emerged. Expand abstract.
10 days ago
7/10 relevant
arXiv

Layered Embeddings for Amodal Instance Segmentation

Results demonstrate that the network can accurately estimate complete masks in the presence of occlusion and outperform leading top-down bounding-box approaches. Expand abstract.
10 days ago
4/10 relevant
arXiv