no code implementations • 22 Dec 2022 • Shu Lok Tsang, Maxwell T. West, Sarah M. Erfani, Muhammad Usman
A subclass of QML methods is quantum generative adversarial networks (QGANs) which have been studied as a quantum counterpart of classical GANs widely used in image manipulation and generation tasks.
no code implementations • 23 Nov 2022 • Maxwell T. West, Sarah M. Erfani, Christopher Leckie, Martin Sevior, Lloyd C. L. Hollenberg, Muhammad Usman
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology and industry.
no code implementations • 30 Oct 2022 • Muhammad Usman, Azka Rehman, Abdullah Shahid, Siddique Latif, Shi Sub Byon, Byoung Dai Lee, Sung Hyun Kim, Byung il Lee, Yeong Gil Shin
Particularly, we exploit Bi-Directional Maximum intensity projection (MIP) images of various thicknesses (i. e., 3, 5 and 10mm) along with a 3D patch of CT scan, consisting of 10 adjacent slices to feed into self-distillation-based Multi-Encoders Network (MEDS-Net).
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 • 6 Oct 2022 • Azka Rehman, Muhammad Usman, Rabeea Jawaid, Amal Muhammad Saleem, Shi Sub Byon, Sung Hyun Kim, Byoung Dai Lee, Byung il Lee, Yeong Gil Shin
In this paper, we propose a novel dual-stage deep learning-based scheme for the automatic segmentation of the mandibular canal.
1 code implementation • 5 Aug 2022 • Muhammad Usman, Youcheng Sun, Divya Gopinath, Rishi Dange, Luca Manolache, Corina S. Pasareanu
Deep neural network (DNN) models, including those used in safety-critical domains, need to be thoroughly tested to ensure that they can reliably perform well in different scenarios.
no code implementations • 1 Jul 2022 • Pei-Yong Wang, Muhammad Usman, Udaya Parampalli, Lloyd C. L. Hollenberg, Casey R. Myers
Quantum algorithms based on variational approaches are one of the most promising methods to construct quantum solutions and have found a myriad of applications in the last few years.
no code implementations • 16 Jun 2022 • Fanzhe Qu, Sarah M. Erfani, Muhammad Usman
However, the impact of coreset selection on the performance of quantum K-Means clustering has not been explored.
no code implementations • 4 Jun 2022 • Xun Zhang, Mathew Schwartz, Muhammad Usman, Petros Faloutsos, Mubbasir Kapadia
In this paper, we focus on the modification of policies that can lead to movement patterns and directional guidance of occupants, which are represented as agents in a 3D simulation engine.
no code implementations • 8 May 2022 • Youcheng Sun, Muhammad Usman, Divya Gopinath, Corina S. Păsăreanu
Neural networks are successfully used in a variety of applications, many of them having safety and security concerns.
no code implementations • 11 Apr 2022 • Muhammad Usman, Jeong-A Lee, Milos D. Ercegovac
Synthesis results of the proposed designs have been presented and compared with the non-pipelined online multiplier, pipelined online multiplier with full working precision and conventional serial-parallel and array multipliers.
1 code implementation • 31 Jan 2022 • Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina S. Pasareanu
For correction, we propose an input correction technique that uses a differential analysis to identify the trigger in the detected poisoned images, which is then reset to a neutral color.
no code implementations • 25 Oct 2021 • Muhammad Usman, Divya Gopinath, Corina S. Păsăreanu
The efficacy of machine learning models is typically determined by computing their accuracy on test data sets.
no code implementations • 12 Oct 2021 • Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman
Surface code error correction offers a highly promising pathway to achieve scalable fault-tolerant quantum computing.
no code implementations • 3 Jun 2021 • Buliao Huang, Yunhui Zhu, Muhammad Usman, Huanhuan Chen
SSCFlow explicitly utilizes the label information to facilitate the imputation and classification simultaneously by estimating the conditional distribution of incomplete instances with a novel semi-supervised normalizing flow.
1 code implementation • 2 Jun 2021 • Syed Saiq Hussain, Muhammad Usman, Taha Hasan Masood Siddique, Imran Naseem, Roberto Togneri, Mohammed Bennamoun
In this research a novel stochastic gradient descent based learning approach for the radial basis function neural networks (RBFNN) is proposed.
no code implementations • 30 Apr 2021 • Mohammad Iman Alizadeh, Muhammad Usman, Florin Capitanescu
To address the latter issue, this paper envisions N-1 security control in RES dominated power systems through stochastic multi-period AC security constrained optimal power flow (SCOPF).
1 code implementation • 23 Mar 2021 • Muhammad Usman, Divya Gopinath, Youcheng Sun, Yannic Noller, Corina Pasareanu
We present novel strategies to enable precise yet efficient repair such as inferring correctness specifications to act as oracles for intermediate layer repair, and generation of experts for each class.
no code implementations • 2 Mar 2021 • Muhammad Usman, Michael Felderer, Michael Unterkalmsteiner, Eriks Klotins, Daniel Mendez, Emil Alegroth
Regulatory compliance is a well-studied area, including research on how to model, check, analyse, enact, and verify compliance of software.
no code implementations • 27 Feb 2021 • Muhammad Usman, Yannic Noller, Corina Pasareanu, Youcheng Sun, Divya Gopinath
This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks.
no code implementations • 8 Jan 2021 • Muhammad Usman, Kashif Ahmad, Amir Sohail, Marwa Qaraqe
In this regard, there is a need to build automatic tools to monitor the blood glucose levels of diabetics and their daily food intake.
no code implementations • 8 Dec 2020 • Vahid Azizi, Muhammad Usman, Honglu Zhou, Petros Faloutsos, Mubbasir Kapadia
We present a floorplan embedding technique that uses an attributed graph to represent the geometric information as well as design semantics and behavioral features of the inhabitants as node and edge attributes.
no code implementations • 24 Sep 2020 • Taha Hasan Masood Siddique, Muhammad Usman
A technique for object localization based on pose estimation and camera calibration is presented.
1 code implementation • 11 Sep 2020 • Shujaat Khan, Muhammad Usman, Abdul Wahab
In this research, we propose a computational framework for the prediction of AFPs which is essentially based on a sample-specific classification method using the sparse reconstruction.
1 code implementation • 19 Aug 2020 • Ziqiang Li, Muhammad Usman, Rentuo Tao, Pengfei Xia, Chaoyue Wang, Huanhuan Chen, Bin Li
Although a handful number of regularization and normalization methods have been proposed for GANs, to the best of our knowledge, there exists no comprehensive survey that primarily focuses on objectives and development of these methods, apart from some in-comprehensive and limited scope studies.
no code implementations • 10 Feb 2020 • Nazar Waheed, Xiangjian He, Muhammad Ikram, Saad Sajid Hashmi, Muhammad Usman
In this paper, we provide a summary of research efforts made in the past few years, starting from 2008 to 2019, addressing security and privacy issues using ML algorithms and BCtechniques in the IoT domain.
no code implementations • 31 Dec 2019 • Muhammad Usman, Byoung-Dai Lee, Shi Sub Byon, Sung Hyun Kim, Byung-ilLee
The proposed technique can be segregated into two stages, at the first stage, it takes a 2-D ROI containing the nodule as input and it performs patch-wise investigation along the axial axis with a novel adaptive ROI strategy.
no code implementations • 25 Dec 2019 • Muhammad Usman, Wenxi Wang, Kaiyuan Wang, Marko Vasic, Haris Vikalo, Sarfraz Khurshid
However, MCML metrics based on model counting show that the performance can degrade substantially when tested against the entire (bounded) input space, indicating the high complexity of precisely learning these properties, and the usefulness of model counting in quantifying the true performance.
1 code implementation • 21 Nov 2019 • Shakeel Muhammad Ibrahim, Muhammad Sohail Ibrahim, Muhammad Usman, Imran Naseem, Muhammad Moinuddin
Heart is one of the vital organs of human body.
no code implementations • 11 Sep 2019 • Muhammad Usman, Jeong A Lee
Antifreeze proteins (AFPs) are the sub-set of ice binding proteins indispensable for the species living in extreme cold weather.
no code implementations • 17 Aug 2019 • Alishba Sadiq, Muhammad Sohail Ibrahim, Muhammad Usman, Muhammad Zubair, Shujaat Khan
The proposed RBF architecture is explored for the prediction of Mackey-Glass time series and results are compared with the standard RBF.
no code implementations • 20 Feb 2019 • Muhammad Usman, Muhammad Umar Farooq, Siddique Latif, Muhammad Asim, Junaid Qadir
The downside of multishot MRI is that it is very sensitive to subject motion and even small amounts of motion during the scan can produce artifacts in the final MR image that may cause misdiagnosis.
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 • 4 Dec 2018 • Alishba Sadiq, Muhammad Usman, Shujaat Khan, Imran Naseem, Muhammad Moinuddin, Ubaid M. Al-Saggaf
The proposed $q$-least mean fourth ($q$-LMF) is an extension of least mean fourth (LMF) algorithm and it is based on the $q$-calculus which is also known as Jackson derivative.
no code implementations • 24 Nov 2018 • Siddique Latif, Muhammad Asim, Muhammad Usman, Junaid Qadir, Rajib Rana
Multishot Magnetic Resonance Imaging (MRI) has recently gained popularity as it accelerates the MRI data acquisition process without compromising the quality of final MR image.
no code implementations • 25 Jan 2018 • Muhammad Usman, Siddique Latif, Junaid Qadir
Feature descriptors involved in image processing are generally manually chosen and high dimensional in nature.
Dimensionality Reduction Facial Expression Recognition (FER)
no code implementations • 25 Jan 2018 • Siddique Latif, Muhammad Usman, Rajib Rana, Junaid Qadir
Our choice of RNNs is motivated by the great success of deep learning in medical applications and by the observation that RNNs represent the deep learning configuration most suitable for dealing with sequential or temporal data even in the presence of noise.