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RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
(
Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...
1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data
(
Elsevier B.V.
, 2018 , Article)
Structural damage detection has been an interdisciplinary area of interest for various engineering fields. While the available damage detection methods have been in the process of adapting machine learning concepts, most ...
Credit default swap pricing using artificial neural networks
(2010 , Conference Paper)
The credit derivatives market has experienced unprecedented growth over the past few years. As such, there is a growing interest in tools for pricing the most prominent credit derivative, the credit default swap. In this ...
Real-time optical character recognition on field programmable gate array for automatic number plate recognition system
(2013 , Article)
The last main stage in an automatic number plate recognition system (ANPRs) is optical character recognition (OCR), where the number plate characters on the number plate image are converted into encoded texts. In this ...
An approach for constructing complex discriminating surfaces based on Bayesian interference of the maximum entropy
(
Elsevier Inc.
, 2003 , Article)
In this paper we present a comprehensive Maximum Entropy (MaxEnt) procedure for the classification tasks. This MaxEnt is applied successfully to the problem of estimating the probability distribution function (pdf) of a ...
Neural network-based model predictive control system for optimizing building automation and management systems of sports facilities
(
Elsevier Ltd
, 2022 , Article)
Sports facilities are considered complex buildings due to their high energy demand and occupancy profiles. Therefore, their management and optimization are crucial for reducing their energy consumption and carbon footprint ...
The influence of aeration scheme and aeration rate on the permeate flux for wastewater treatment using membrane bioreactors: Experimental and artificial neural network modeling
(
Desalination Publications
, 2021 , Article)
In this paper, the effect of time, aeration scheme, aeration rate, and mixed liquor suspended solid (MLSS) concentration on the permeate flux in membrane bioreactors have been studied. Aeration rates of 0.5, 1.0, and 1.5 ...
Identifying crack parameters in slow rotating machinery using vibration measurements and hybrid neuro-particle swarm technique
(2010 , Conference Paper)
Low-cycle fatigue-initiated cracks may result in failure in slow-rotating equipments. Online monitoring to identify such fault/crack parameters, namely crack size and crack location, would be critical in providing an early ...
A neural network algorithm for hardware-software verification
(
IEEE
, 2003 , Conference Paper)
Formal verification is the task of proving that a property holds for a model of a design. This paper examines the idea of a Neural Network-based algorithm used to find the set of states that makes a specification valid. ...
Reveal the hidden layer via entity embedding in traffic prediction
(
Elsevier B.V.
, 2019 , Conference Paper)
The neural network-based models have been widely used in traffic prediction. They have improved accuracy and efficiency in traffic flow, speed, passenger flow, and delay. Many variables are considered to predict traffic ...