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Soheil Varastehpour
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2020 – today
- 2024
- [c9]Seloua Haddaoui, Nawres Khlifa, Salim Chikhi, Soheil Varastehpour, Fouzia Adjailia:
A Comprehensive Review of Beekeeping Datasets for Precision Apiculture Research. CoDIT 2024: 2043-2048 - 2023
- [c8]Iman Ardekani, Hamid R. Sharifzadeh, Soheil Varastehpour:
Dynamic Control of Active Noise Control Systems with Simplified Secondary Path Models. GCCE 2023: 424-425 - [c7]Iman Ardekani, Soheil Varastehpour, Hamid R. Sharifzadeh, Waleed H. Abdulla:
Improving ANC Computational Efficiency: A Novel Fx LMS Algorithm with Dynamic Response Control. M2VIP 2023: 1-6 - [c6]Changjin Wang, Hamid R. Sharifzadeh, Soheil Varastehpour, Iman Ardekani:
Analysis and Comparison of Deepfakes Detection Methods for Cross-Library Generalisation. PST 2023: 1-7
2010 – 2019
- 2019
- [c5]Soheil Varastehpour, Hamid R. Sharifzadeh, Iman Ardekani, Xavier Francis:
Vein Pattern Visualisation and Feature Extraction using Sparse Auto-Encoder for Forensic Purposes. AVSS 2019: 1-8 - [c4]Xavier Francis, Hamid R. Sharifzadeh, Angus Newton, Nilufar Baghaei, Soheil Varastehpour:
Feature Enhancement and Denoising of a Forensic Shoeprint Dataset for Tracking Wear-And-Tear Effects. ISSPIT 2019: 1-5 - [c3]Soheil Varastehpour, Hamid R. Sharifzadeh, Iman Ardekani, Xavier Francis, Nilufar Baghaei:
An Adaptive Method for Vein Recognition Enhancement Using Deep Learning. ISSPIT 2019: 1-6 - [c2]Xavier Francis, Hamid R. Sharifzadeh, Angus Newton, Nilufar Baghaei, Soheil Varastehpour:
Learning Wear Patterns on Footwear Outsoles Using Convolutional Neural Networks. TrustCom/BigDataSE 2019: 450-457 - [i1]Xavier Francis, Hamid R. Sharifzadeh, Angus Newton, Nilufar Baghaei, Soheil Varastehpour:
Learning Wear Patterns on Footwear Outsoles Using Convolutional Neural Networks. CoRR abs/1907.12005 (2019) - 2018
- [c1]Soheil Varastehpour, Hamid R. Sharifzadeh, Iman Ardekani, Abdolhossein Sarrafzadeh:
Extended Abstract: A Review of Biometric Traits with Insight into Vein Pattern Recognition. PST 2018: 1-2
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last updated on 2024-11-13 23:50 CET by the dblp team
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