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20172025
most citedSemi-supervised Classification: Cluster and Label Approach using Particle Swarm Optimization

6 citations · 19 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC2025

A Fuzzy Set-based Approach for Matching Hand-Drawing Shapes of Touch-based Gestures for Graphical Passwords

Adel Sabour, Ahmed Gadallah, Hesham Hefny

This paper presents a two-dimension fuzzy set based approach for matching touch-based gestures using fuzzy cued click point technique. The pro posed approach aims mainly to improve…

cs.NI2022★ 5 cited

F-802.11P: A Fuzzy Enhancement for ieee 802.11P in Vehicle-TO-Everything Communications

Hamdy A. M. Sayedahmed, Emadeldin M. Elgamal, Hesham A. Hefny

Vehicle-to-Everything communications (V2X) are becoming increasingly popular as a solution for safer roads and better traffic management. One of the essential protocols in V2X is t…

cs.NI2022★ 5 cited

A Proposed Fuzzy Logic Approach for Conserving the Energy of Data Transmission in the Temperature Monitoring Systems of Internet of Things

Noha Elqeblawy, Ammar Mohammed, Hesham A. Hefny

One of the primary challenges facing the Internet of Things is the reservation and efficient consumption of energy resources, especially in those types of applications that require…

cs.LG2017★ 2 cited

Center of Gravity PSO for Partitioning Clustering

Shahira Shaaban Azab, Hesham Ahmed Hefny

This paper presents the local best model of PSO for partition-based clustering. The proposed model gets rid off the drawbacks of gbest PSO for clustering. The model uses a pre-spec…

cs.LG2017★ 1 cited

Swarm Intelligence in Semi-supervised Classification

Shahira Shaaban Azab, Hesham Ahmed Hefny

This Paper represents a literature review of Swarm intelligence algorithm in the area of semi-supervised classification. There are many research papers for applying swarm intellige…

cs.LG2017★ 6 cited

Semi-supervised Classification: Cluster and Label Approach using Particle Swarm Optimization

Shahira Shaaban Azab, Mohamed Farouk Abdel Hady, Hesham Ahmed Hefny

Classification predicts classes of objects using the knowledge learned during the training phase. This process requires learning from labeled samples. However, the labeled samples…