Muhammad Usman Tariq

Orcid: 0000-0002-7605-3040

According to our database1, Muhammad Usman Tariq authored at least 16 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
A hybrid model for energy-efficient Green Internet of Things enabled intelligent transportation systems using federated learning.
Internet Things, April, 2024

Accurate Wheat Yield Prediction Using Machine Learning and Climate-NDVI Data Fusion.
IEEE Access, 2024

2023
An Optimized IoT-Enabled Big Data Analytics Architecture for Edge-Cloud Computing.
IEEE Internet Things J., March, 2023

Image Encryption Scheme Based on Orbital Shift Pixels Shuffling with ILM Chaotic System.
Entropy, 2023

Compiling Recurrences over Dense and Sparse Arrays.
CoRR, 2023

Multi-Input Deep Learning Approach for Breast Cancer Screening Using Thermal Infrared Imaging and Clinical Data.
IEEE Access, 2023

Pre-Trained Model-Based NFR Classification: Overcoming Limited Data Challenges.
IEEE Access, 2023

2022
Smart teledentistry healthcare architecture for medical big data analysis using IoT-enabled environment.
Sustain. Comput. Informatics Syst., 2022

2021
BP Neural Network Combination Prediction for Big Data Enterprise Energy Management System.
Mob. Networks Appl., 2021

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey.
IEEE Access, 2021

Graph Theoretic Approach for the Analysis of Comprehensive Mass-Spectrometry (MS/MS) Data of Dissolved Organic Matter.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
An Improved Framework for Modelling Data Warehouse Systems Using UML Profile.
Int. Arab J. Inf. Technol., July, 2020

Human Proteome and Peptides.
Dataset, January, 2020

SafeCity: Toward Safe and Secured Data Management Design for IoT-Enabled Smart City Planning.
IEEE Access, 2020

2018
Parallel Sampling-Pipeline for Indefinite Stream of Heterogeneous Graphs using OpenCL for FPGAs.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Power-efficient and highly scalable parallel graph sampling using FPGAs.
Proceedings of the International Conference on ReConFigurable Computing and FPGAs, 2017


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