no code implementations • 23 Apr 2024 • Mona Alzahrani, Muhammad Usman, Salma Kammoun, Saeed Anwar, Tarek Helmy
We provide detailed information about existing deep learning-based and transformer-based multi-view 3D object recognition models, including the most commonly used 3D datasets, camera configurations and number of views, view selection strategies, pre-trained CNN architectures, fusion strategies, and recognition performance on 3D classification and 3D retrieval tasks.
no code implementations • 3 Mar 2024 • Zeheng Wang, James Cooper, Muhammad Usman, Timothy van der Laan
The rapid advancement of Internet of Things (IoT) necessitates the development of optimized Chemiresistive Sensor (CRS) arrays that are both energy-efficient and capable.
no code implementations • 13 Dec 2023 • Yanqiu Wu, Eromanga Adermann, Chandra Thapa, Seyit Camtepe, Hajime Suzuki, Muhammad Usman
Our extensive simulation results present that attacks generated on QVCs transfer well to CNN models, indicating that these adversarial examples can fool neural networks that they are not explicitly designed to attack.
no code implementations • 6 Dec 2023 • Canaan Yung, Muhammad Usman
In this work, we propose solving the k-means clustering problem with the variational quantum eigensolver (VQE) and a customised coreset method, the Contour coreset, which has been formulated with specific focus on quantum algorithms.
no code implementations • 26 Sep 2023 • Che-Jui Chang, Samuel S. Sohn, Sen Zhang, Rajath Jayashankar, Muhammad Usman, Mubbasir Kapadia
We have conducted a user study with 199 participants to assess how the average person judges the affects perceived from multimodal behaviors that are consistent and inconsistent with respect to a driving affect.
no code implementations • 12 Sep 2023 • Muhammad Sohail Ibrahim, Muhammad Usman, Malik Zohaib Nisar, Jeong-A Lee
We propose a Digit-Serial Left-tO-righT (DSLOT) arithmetic based processing technique called DSLOT-NN with aim to accelerate inference of the convolution operation in the deep neural networks (DNNs).
no code implementations • 23 Aug 2023 • Natasha Latif, Shafqat Ali Shad, Muhammad Usman, Chandan Kumar, Bahman B Motii, MD Mahfuzer Rahman, Khuram Shafi, Zahra Idrees
In this paper, we price European Call three different option pricing models, where the volatility is dynamically changing i. e. non constant.
no code implementations • 14 Aug 2023 • Muhammad Zeeshan, Saima Masood, Saima Ashraf, Shehla G. Bokhar, Hafsa Zainab, Saher Ijaz, Muhammad Usman, Ayesha Masood, Hafiz Faseeh U. Rehman, Mirza M. Usman
Histomorphological evaluation of rumen mucosal epithelium showed a significant improvement in the mixed-supplemented group (P<0. 05) as compared to the yeast-supplemented and control groups.
1 code implementation • 12 Jul 2023 • Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, Muhammad Usman, Naveed Akhtar, Nick Barnes, Ajmal Mian
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond.
no code implementations • 22 Jun 2023 • Maxwell T. West, Shu-Lok Tsang, Jia S. Low, Charles D. Hill, Christopher Leckie, Lloyd C. L. Hollenberg, Sarah M. Erfani, Muhammad Usman
Machine learning algorithms are powerful tools for data driven tasks such as image classification and feature detection, however their vulnerability to adversarial examples - input samples manipulated to fool the algorithm - remains a serious challenge.
no code implementations • 13 Jun 2023 • Pawan Kumar Sarika, Deepika Badampudi, Sai Prashanth Josyula, Muhammad Usman
Kubernetes is a free, open-source container orchestration system for deploying and managing Docker containers that host microservices.
no code implementations • 9 Jun 2023 • Shahzaib Iqbal, Tariq M. Khan, Syed S. Naqvi, Muhammad Usman, Imran Razzak
The results demonstrate the robustness, generalizability, and high segmentation accuracy of LDMRes-Net, positioning it as an efficient tool for accurate and rapid medical image segmentation in diverse clinical applications, particularly on IoT and edge platforms.
no code implementations • 6 Apr 2023 • Muhammad Usman, Milos Ercegovac, Jeong-A Lee
Serial nature of the online algorithm and gradual increment/decrement of active slices minimize the interconnects and signal activities resulting in overall reduction of area and power consumption.
no code implementations • 4 Apr 2023 • Muhammad Usman, Azka Rehman, Abdullah Shahid, Siddique Latif, Shi Sub Byon, Sung Hyun Kim, Tariq Mahmood Khan, Yeong Gil Shin
By employing a novel adaptive hard attention mechanism, MESAHA-Net iteratively performs slice-by-slice 2D segmentation of lung nodules, focusing on the nodule region in each slice to generate 3D volumetric segmentation of lung nodules.
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.
1 code implementation • 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 • 25 May 2021 • Zeheng Wang, Liang Li, Ross C. C. Leon, Jinlin Yang, Junjie Shi, Timothy van der Laan, Muhammad Usman
The inherent flexibility of our approach allows easy adaptation to various tasks, thus making it highly relevant to many applications of the semiconductor industry.
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.
Software Engineering
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.
Generative Adversarial Network Motion Correction In Multishot Mri +1
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.
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.