プロフィール詳細

プロジェクトを作成

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Dr. salman k.に依頼

United Kingdom

Computer Vision Expert

プロフィール概要

I received my Master’s degree in Computer Vision from Sejong University, Seoul, Republic of Korea in 2020 with research in vision-based fire/smoke detection. Currently, I am pursuing PhD degree in Computer Vision (Deep Learning for Modelling Complex Video Activities) from Oxford Brookes University, Oxford, United Kingdom. I am working as a research assistant at Visual Artificial Intelligence Laboratory (VAIL) from February 2020. I have published several papers in well-reputed journals including IEEE IoTJ, TII, Elsevier PRL, and JOCS. I am also serving as a reviewer in reputed journals including IEEE TII, Access, and IoTJ. My research interests include Complex Video Actions/Activities Recognition, Fire/Smoke Scene Analysis, Medical Image Analysis, Computer Vision, Deep Learning, Video Surveillance, IoT, and Smart Cities.

専門分野

• ★ Computer Vision
• ☆ Data Science
• ☆ Image Processing
• ☆ Machine Learning
• ☆ Deep Learning

サービス

• Writing
• Research
• Data & AI

Writing Technical Writing

Research Secondary Data Collection

Data & AI Statistical Analysis, Algorithm Design-Non ML

職務経験

Research Assistant

Oxford Brookes University

2月 2020 - 現在

Research Assistant

Sejong University

3月 2018 - 2月 2020

学歴

PhD Degree in Computer Vision (Deep Learning for Modelling Complex Video Activities) (SCHOOL OF ENGINEERING, COMPUTING AND MATHEMATICS)

Oxford Brookes University

2月 2020 - 現在

Master's (Software Convergence)

Sejong University

3月 2018 - 2月 2020

BS Computer Science (Computer Science)

Islamia College University

6月 2013 - 8月 2017

認定資格

• 認定資格の詳細は未入力です。

出版物

JOURNAL ARTICLE

(2020). Vision-based personalized Wireless Capsule Endoscopy for smart healthcare: Taxonomy, literature review, opportunities and challenges . Future Generation Computer Systems.

Salman Khan, Khan Muhammad, Vasile Palade, Irfan Mehmood, Victor Hugo C. de Albuquerque(2020). Edge Intelligence-Assisted Smoke Detection in Foggy Surveillance Environments . {IEEE} Transactions on Industrial Informatics. 16. (2). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1067--1075. Institute of Electrical and Electronics Engineers ({IEEE})

Salman Khan, Khan Muhammad, Javier Del Ser, Victor Hugo C. de Albuquerque(2020). Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey . {IEEE} Transactions on Neural Networks and Learning Systems. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1--16. Institute of Electrical and Electronics Engineers ({IEEE})

Salman Khan, Khan Muhammad, Shahid Mumtaz, Sung Wook Baik, Victor Hugo C. de Albuquerque(2019). Energy-Efficient Deep {CNN} for Smoke Detection in Foggy {IoT} Environment . {IEEE} Internet of Things Journal. 6. (6). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 9237--9245. Institute of Electrical and Electronics Engineers ({IEEE})

Salman Khan, Khan Muhammad, Mohamed Elhoseny, Syed Hassan Ahmed, Sung Wook Baik(2019). Efficient Fire Detection for Uncertain Surveillance Environment . {IEEE} Transactions on Industrial Informatics. 15. (5). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 3113--3122. Institute of Electrical and Electronics Engineers ({IEEE})

(2019). Edge Intelligence-Assisted Smoke Detection in Foggy Surveillance Environments .

(2019). Energy-Efficient Deep CNN for Smoke Detection in Foggy IoT Environment .

(2019). Intelligent Baby Behavior Monitoring using Embedded Vision in IoT for Smart Healthcare Centers . Journal of Artificial Intelligence and Systems.

Sajjad, M., Khan, S., Muhammad, K., Wu, W., Ullah, A., Baik, S.W.(2019). Multi-grade brain tumor classification using deep CNN with extensive data augmentation . Journal of Computational Science. 30. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 174-182.

Muhammad Sajjad and Salman Khan and Tanveer Hussain and Khan Muhammad and Arun Kumar Sangaiah and Aniello Castiglione and Christian Esposito and Sung Wook Baik(2018). CNN-based anti-spoofing two-tier multi-factor authentication system . Pattern Recognition Letters.

Sajjad, M., Khan, S., Hussain, T., Muhammad, K., Sangaiah, A.K., Castiglione, A., Esposito, C., Baik, S.W.(2018). CNN-based anti-spoofing two-tier multi-factor authentication system . Pattern Recognition Letters.