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An Empirical Study for PCA- and LDA-Based Feature Reduction for Gas Identification

IEEE sensors journal, 2016-07, Vol.16 (14), p.5734-5746

2016

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Embedded Platform for Gas Applications Using Hardware/Software Co-Design and RFID

IEEE sensors journal, 2018-06, Vol.18 (11), p.4633-4642

2018

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Deep Learning for Ultrasonic Crack Characterization in NDE

IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2021-05, Vol.68 (5), p.1854-1865

2021

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Uncertainty Quantification for Deep Learning in Ultrasonic Crack Characterization

IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2022-07, Vol.69 (7), p.2339-2351

2022

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MLP Neural Network Based Gas Classification System on Zynq SoC

IEEE access, 2016, Vol.4, p.8138-8146

2016

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ECG encryption and identification based security solution on the Zynq SoC for connected health systems

Journal of parallel and distributed computing, 2017-08, Vol.106, p.143-152

2017

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Domain Adapted Deep-Learning for Improved Ultrasonic Crack Characterization Using Limited Experimental Data

IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2022-04, Vol.69 (4), p.1485-1496

2022

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Compressive sensing based electronic nose platform

Digital signal processing, 2017-01, Vol.60, p.350-359

2017

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Electronic nose system on the Zynq SoC platform

Microprocessors and microsystems, 2017-08, Vol.53, p.145-156

2017

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An Empirical Study for Quantification of Carcinogenic Formaldehyde by Integrating a Probabilistic Framework with Spike Latency Patterns in an Electronic Nose

Sensors & transducers, 2015-10, Vol.193 (10), p.86-86

2015

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Gas Identification Using Passive UHF RFID Sensor Platform

Sensors & transducers, 2015-11, Vol.194 (11), p.42-42

2015

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An interactive software tool for gas identification

Journal of natural gas science and engineering, 2018-07, Vol.55, p.612-624

2018

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HW/SW co-design based implementation of Gas discrimination

2016 IEEE 27th International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2016, p.237-238

2016

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Gas identification in electronic nose by using similarity measure between latency patterns

2014 26th International Conference on Microelectronics (ICM), 2014, p.200-203

2014

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High Level Synthesis Based E-Nose System for Gas Applications

2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2016, p.202-203

2016

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Heterogeneous Implementation of ECG Encryption and Identification on the Zynq SoC

2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2016, p.139-139

2016

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DESIGN AND IMPLEMENTATION OF A GAS IDENTIFICATION SYSTEM ON ZYNQ SOC PLATFORM

ARPN journal of engineering and applied sciences, 2015-11, Vol.10 (20), p.9758-9764

2015

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Custom ip cores for robust data analysis and pattern recognition algorithms

Ait Si Ali, Amine

2016

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Enhanced Biometric Security and Privacy Using ECG on the Zynq SoC

Biometric Security and Privacy, 2016, p.179-202

2016

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Design and Performance Evaluation of a Committee Machine for Gas Identification

Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016, 2018, Vol.16, p.936-945

2018

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A Reconfigurable Connected Health Platform Using ZYNQ System on Chip

Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016, 2018, Vol.16, p.857-867

2018

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Generalised and Versatile Connected Health Solution on the Zynq SoC

Intelligent Systems and Applications, 2017, Vol.751, p.454-474

2017

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Extensive Data Exploration for Automatic Price Suggestion Using Item Description: Case Study for the Kaggle Mercari Challenge

Proceedings of the 2nd International Conference on Advances in Artificial Intelligence, 2018, p.41-45

2018

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Gas identification with spike codes in wireless electronic nose: A potential application for smart green buildings

2015 SAI Intelligent Systems Conference (IntelliSys), 2015, p.457-462

2015

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Computationally efficient environmental monitoring with electronic nose: A potential technology for ambient assisted living

2016 IEEE International Symposium on Systems Engineering (ISSE), 2016, p.1-4

2016

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An Empirical Study for PCA- and LDA-Based Feature Reduction for Gas Identification

Embedded Platform for Gas Applications Using Hardware/Software Co-Design and RFID

Deep Learning for Ultrasonic Crack Characterization in NDE

Uncertainty Quantification for Deep Learning in Ultrasonic Crack Characterization

MLP Neural Network Based Gas Classification System on Zynq SoC

ECG encryption and identification based security solution on the Zynq SoC for connected health systems

Domain Adapted Deep-Learning for Improved Ultrasonic Crack Characterization Using Limited Experimental Data

Compressive sensing based electronic nose platform

Electronic nose system on the Zynq SoC platform

An Empirical Study for Quantification of Carcinogenic Formaldehyde by Integrating a Probabilistic Framework with Spike Latency Patterns in an Electronic Nose

Gas Identification Using Passive UHF RFID Sensor Platform

An interactive software tool for gas identification

HW/SW co-design based implementation of Gas discrimination

Gas identification in electronic nose by using similarity measure between latency patterns

High Level Synthesis Based E-Nose System for Gas Applications

Heterogeneous Implementation of ECG Encryption and Identification on the Zynq SoC

DESIGN AND IMPLEMENTATION OF A GAS IDENTIFICATION SYSTEM ON ZYNQ SOC PLATFORM

Custom ip cores for robust data analysis and pattern recognition algorithms

Enhanced Biometric Security and Privacy Using ECG on the Zynq SoC

Design and Performance Evaluation of a Committee Machine for Gas Identification

A Reconfigurable Connected Health Platform Using ZYNQ System on Chip

Generalised and Versatile Connected Health Solution on the Zynq SoC

Extensive Data Exploration for Automatic Price Suggestion Using Item Description: Case Study for the Kaggle Mercari Challenge

Gas identification with spike codes in wireless electronic nose: A potential application for smart green buildings

Computationally efficient environmental monitoring with electronic nose: A potential technology for ambient assisted living

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