1 code implementation • 24 Mar 2017 • Adnan Qayyum, Syed Muhammad Anwar, Muhammad Awais, Muhammad Majid
The learned features and the classification results are used to retrieve medical images.
no code implementations • 4 Sep 2017 • Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum, Muhammad Awais, Majdi Alnowami, Muhammad Khurram Khan
Deep learning is successfully used as a tool for machine learning, where a neural network is capable of automatically learning features.
1 code implementation • 15 Dec 2018 • Siddique Latif, Adnan Qayyum, Muhammad Usman, Junaid Qadir
Cross-lingual speech emotion recognition is an important task for practical applications.
no code implementations • 29 May 2019 • Adnan Qayyum, Muhammad Usama, Junaid Qadir, Ala Al-Fuqaha
Connected and autonomous vehicles (CAVs) will form the backbone of future next-generation intelligent transportation systems (ITS) providing travel comfort, road safety, along with a number of value-added services.
no code implementations • 21 Jan 2020 • Adnan Qayyum, Junaid Qadir, Muhammad Bilal, Ala Al-Fuqaha
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CADx) using multi-dimensional medical images.
no code implementations • 4 Feb 2020 • Khansa Rasheed, Adnan Qayyum, Junaid Qadir, Shobi Sivathamboo, Patrick Kwan, Levin Kuhlmann, Terence O'Brien, Adeel Razi
Here we provide a comprehensive review of state-of-the-art ML techniques in early prediction of seizures using EEG signals.
no code implementations • 24 Dec 2020 • Muhammad Ahtazaz Ahsan, Adnan Qayyum, Junaid Qadir, Adeel Razi
In recent years, deep learning (DL) techniques have provided state-of-the-art performance on different medical imaging tasks.
no code implementations • 19 Jan 2021 • Adnan Qayyum, Kashif Ahmad, Muhammad Ahtazaz Ahsan, Ala Al-Fuqaha, Junaid Qadir
Despite significant improvements over the last few years, cloud-based healthcare applications continue to suffer from poor adoption due to their limitations in meeting stringent security, privacy, and quality of service requirements (such as low latency).
no code implementations • 24 Oct 2022 • Adnan Qayyum, Muhammad Atif Butt, Hassan Ali, Muhammad Usman, Osama Halabi, Ala Al-Fuqaha, Qammer H. Abbasi, Muhammad Ali Imran, Junaid Qadir
Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalised experiences to socialize, work, and play in self-sustaining and hyper-spatio-temporal virtual world(s).
no code implementations • 25 Mar 2023 • Adnan Qayyum, Muhammad Bilal, Muhammad Hadi, Paweł Capik, Massimo Caputo, Hunaid Vohra, Ala Al-Fuqaha, Junaid Qadir
Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science.
no code implementations • 11 May 2023 • Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Max Berniker, Ziheng Wang, Rogerio Nespolo, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Bo Liu, David Austin, Yiheng Wang, Michal Futrega, Jean-Francois Puget, Zhenqiang Li, Yoichi Sato, Ryo Fujii, Ryo Hachiuma, Mana Masuda, Hideo Saito, An Wang, Mengya Xu, Mobarakol Islam, Long Bai, Winnie Pang, Hongliang Ren, Chinedu Nwoye, Luca Sestini, Nicolas Padoy, Maximilian Nielsen, Samuel Schüttler, Thilo Sentker, Hümeyra Husseini, Ivo Baltruschat, Rüdiger Schmitz, René Werner, Aleksandr Matsun, Mugariya Farooq, Numan Saaed, Jose Renato Restom Viera, Mohammad Yaqub, Neil Getty, Fangfang Xia, Zixuan Zhao, Xiaotian Duan, Xing Yao, Ange Lou, Hao Yang, Jintong Han, Jack Noble, Jie Ying Wu, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Herag Arabian, Ning Ding, Knut Moeller, Weiliang Chen, Quan He, Muhammad Bilal, Taofeek Akinosho, Adnan Qayyum, Massimo Caputo, Hunaid Vohra, Michael Loizou, Anuoluwapo Ajayi, Ilhem Berrou, Faatihah Niyi-Odumosu, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
no code implementations • 3 Jul 2023 • Adnan Qayyum, Hassan Ali, Massimo Caputo, Hunaid Vohra, Taofeek Akinosho, Sofiat Abioye, Ilhem Berrou, Paweł Capik, Junaid Qadir, Muhammad Bilal
In this paper, we propose a systematic methodology for developing robust models for surgical tool detection using noisy data.
1 code implementation • 11 Jul 2023 • Hassan Ali, Adnan Qayyum, Ala Al-Fuqaha, Junaid Qadir
Secondly, we utilize the framework to propose two novel attacks: (1) Adversarial Membership Inference Attack (AMIA) efficiently utilizes the membership and the non-membership information of the subjects while adversarially minimizing a novel loss function, achieving 6% TPR on both Fashion-MNIST and MNIST datasets; and (2) Enhanced AMIA (E-AMIA) combines EMIA and AMIA to achieve 8% and 4% TPRs on Fashion-MNIST and MNIST datasets respectively, at 1% FPR.
no code implementations • 11 Aug 2023 • Muhammad Atif Butt, Hassan Ali, Adnan Qayyum, Waqas Sultani, Ala Al-Fuqaha, Junaid Qadir
Semantic understanding of roadways is a key enabling factor for safe autonomous driving.
no code implementations • 19 Sep 2023 • Mahdi Alkaeed, Adnan Qayyum, Junaid Qadir
In this paper, we explore various privacy challenges that future metaverses are expected to face, given their reliance on AI for tracking users, creating XR and MR experiences, and facilitating interactions.
no code implementations • 5 Oct 2023 • Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali, Mohamed Abdallah, Junaid Qadir, Dinh Thai Hoang, Dusit Niyato, Ala Al-Fuqaha
This paper encompasses a taxonomy that highlights the emergence of AdvML4G, a discussion of the differences and similarities between AdvML4G and AdvML, a taxonomy covering social good-related concepts and aspects, an exploration of the motivations behind the emergence of AdvML4G at the intersection of ML4G and AdvML, and an extensive summary of the works that utilize AdvML4G as an auxiliary tool for innovating pro-social applications.
no code implementations • 27 Oct 2023 • Muhammad Bilal, Dinis Martinho, Reiner Sim, Adnan Qayyum, Hunaid Vohra, Massimo Caputo, Taofeek Akinosho, Sofiat Abioye, Zaheer Khan, Waleed Niaz, Junaid Qadir
This study introduces an end-to-end machine learning solution developed as part of our solution for the MICCAI 2023 Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs (ARCADE) challenge, which aims to benchmark solutions for multivessel coronary artery segmentation and potential stenotic lesion localisation from X-ray coronary angiograms.
Ranked #3 on Coronary Artery Segmentation on ARCADE
no code implementations • 23 Nov 2023 • Adam Byfield, William Poulett, Ben Wallace, Anusha Jose, Shatakshi Tyagi, Smita Shembekar, Adnan Qayyum, Junaid Qadir, Muhammad Bilal
Machine learning (ML) models are becoming integral in healthcare technologies, presenting a critical need for formal assurance to validate their safety, fairness, robustness, and trustworthiness.