10 citations · 15 across the 5 of their papers we have counts for
6 papers
Theoretical Convergence of SMOTE-Generated Samples
Firuz Kamalov, Hana Sulieman, Witold Pedrycz
Imbalanced data affects a wide range of machine learning applications, from healthcare to network security. As SMOTE is one of the most popular approaches to addressing this issue,…
Global Pandemics Influence on Cyber Security and Cyber Crimes
Somya Khatri, Aswani Kumar Cherukuri, Firuz Kamalov
COVID-19 has caused widespread damage across many areas of life and has made humans more dependent on the internet and technology making us realize the importance of secure remote…
e-Inu: Simulating A Quadruped Robot With Emotional Sentience
Abhiruph Chakravarty, Jatin Karthik Tripathy, Sibi Chakkaravarthy S +4
Quadruped robots are currently used in industrial robotics as mechanical aid to automate several routine tasks. However, presently, the usage of such a robot in a domestic setting…
Synthetic Data for Feature Selection
Firuz Kamalov, Hana Sulieman, Aswani Kumar Cherukuri
Feature selection is an important and active field of research in machine learning and data science. Our goal in this paper is to propose a collection of synthetic datasets that ca…
Time series signal recovery methods: comparative study
Firuz Kamalov, Hana Sulieman
Signal data often contains missing values. Effective replacement (imputation) of the missing values can have significant positive effects on processing the signal. In this paper, w…
Machine learning applications for COVID-19: A state-of-the-art review
Firuz Kamalov, Aswani Cherukuri, Hana Sulieman +2
The COVID-19 pandemic has galvanized the machine learning community to create new solutions that can help in the fight against the virus. The body of literature related to applicat…