Academic Articles & Research Papers

Intrusion Detection with Neural Networks

With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is through monitoring unusual user activity. Methods of intrusio...

The Handbook of brain theory and neural networks

A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks. Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook ...

The Handbook of brain theory and neural networks

From the Publisher: Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields ...

Optimization of Communication Schemes for DMA-Controlled Accelerators

The hardware accelerator controlled by direct memory access (DMA) is greatly influenced by the communication bandwidth from/to DRAM through on-chip buses. This paper proposes a novel performance estimation algorithm to optimize the communic...

Computational Hyperspectral Camera Design Based on Co-Modulation of Diffractive Optical Element and Superposition Fabry-Perot Filter Array

Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy ha...

Distributed Multi-Agent Deep Reinforcement Learning-Based Transmit Power Control in Cellular Networks

In a multi-cell network, interference management between adjacent cells is a key factor that determines the performance of the entire cellular network. In particular, in order to control inter-cell interference while providing a high data r...

Acoustic Impedance Inversion from Seismic Imaging Profiles Using Self Attention U-Net

Seismic impedance inversion is a vital way of geological interpretation and reservoir investigation from a geophysical perspective. However, it is inevitably an ill-posed problem due to the noise or the band-limited characteristic of seismi...

Intelligent diagnosis with Chinese electronic medical records based on convolutional neural networks

Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...

Rethinking Gated Recurrent Units for Rotating Machinery Prognostics: A Physics-Consistency Benchmark on the Mismatch Between Gating Mechanisms and Degradation Dynamics

Rotating machinery prognostics is essential for ensuring the reliability and operational safety of industrial systems. Although gated recurrent units (GRUs) have achieved competitive performance in remaining useful life (RUL) prediction, wh...

An overview of deep learning in medical imaging focusing on MRI

What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...

Deep learning: a statistical viewpoint

The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...

Rider Optimization With Deep Learning Based Image Encryption for Secure Drone Communication

In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...

A BigBiGAN-Based Loop Closure Detection Algorithm for Indoor Visual SLAM

Loop closure detection serves as the fulcrum of improving the accuracy and precision in simultaneous localization and mapping (SLAM). The majority of loop detection methods extract artificial features, which fall short of learning comprehen...

Gene expression inference with deep learning

MOTIVATION: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dro...

Computational Linguistics and Deep Learning

Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...

Deep Learning for Entity Matching

Entity matching (EM) finds data instances that refer to the same real-world entity. In this paper we examine applying deep learning (DL) to EM, to understand DL's benefits and limitations. We review many DL solutions that have been develope...

Recurrent Neural Networks Based Online Behavioural Malware Detection Techniques for Cloud Infrastructure

Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...

Diacylglycerol kinase kappa is a target of the Prader-Willi syndrome gene SNORD116.

Consistent Fully Automatic Image Colorization Due to Bridging Fully Automatic and Point Interactive Models

Image colorization is a fundamental task in computer vision that aims to predict the missing color channels from grayscale images. In recent years, fully automatic approaches based on deep learning have become the dominant paradigm. However...

Does the direct anterior learning curve persist after fellowship training? A single-center comparative cohort study.