Azim Akhtarshenas

ORCID: 0000-0002-5511-1010
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Research Areas
  • Wireless Signal Modulation Classification
  • Advanced SAR Imaging Techniques
  • Privacy-Preserving Technologies in Data
  • UAV Applications and Optimization
  • Cryptography and Data Security
  • Identification and Quantification in Food
  • Data Mining Algorithms and Applications
  • Imbalanced Data Classification Techniques
  • Industrial Automation and Control Systems
  • Internet Traffic Analysis and Secure E-voting
  • Experimental Learning in Engineering
  • Mobile Crowdsensing and Crowdsourcing
  • Data Stream Mining Techniques
  • Advanced Data Processing Techniques
  • Water Quality Monitoring Technologies
  • Ichthyology and Marine Biology

Universitat Politècnica de València
2024

University of Tehran
2022

Abstract In this paper, we mainly intend to address the underwater image classification problem in an open-set scenario. Image algorithms have been mostly provided with a small set of species, while there exist lots species not available or even unknown ourselves. Thus, deal and extremely high false alarm rate real scenarios, especially case unseen species. Motivated by these challenges, our proposed scheme aims prevent from going classifier section. To end, introduce new framework based on...

10.1007/s42452-022-05105-w article EN cc-by SN Applied Sciences 2022-07-19

In this research paper, we introduce a novel classification method aimed at improving the performance of K-Nearest Neighbors (KNN) algorithm. Our approach leverages Mutual Information (MI) to enhance significance weights and draw inspiration from Shapley values, concept originating cooperative game theory, refine value allocation. The fundamental underlying KNN is samples based on majority thorough their k-nearest neighbors. While both distances labels these neighbors are crucial,...

10.48550/arxiv.2312.01991 preprint EN other-oa arXiv (Cornell University) 2023-01-01

Optimizing the design, performance, and resource efficiency of wireless networks (WNs) necessitates ability to discern Line Sight (LoS) Non-Line (NLoS) scenarios across diverse applications environments. Unmanned Aerial Vehicles (UAVs) exhibit significant potential in this regard due their rapid mobility, aerial capabilities, payload characteristics. Particularly, UAVs can serve as vital non-terrestrial base stations (NTBS) event terrestrial station (TBS) failures or downtime. In paper, we...

10.48550/arxiv.2405.16697 preprint EN arXiv (Cornell University) 2024-05-26

In the realm of machine learning (ML) systems featuring client-host connections, enhancement privacy security can be effectively achieved through federated (FL) as a secure distributed ML methodology. FL integrates cloud infrastructure to transfer models onto edge servers using blockchain technology. Through this mechanism, it guarantees streamlined processing and data storage requirements both centralized decentralized systems, with an emphasis on scalability, considerations, cost-effective...

10.48550/arxiv.2310.05269 preprint EN other-oa arXiv (Cornell University) 2023-01-01
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