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MNIST Fashion Classification Using Quantum Convolutional Neural Networks

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MNIST Fashion Classification Using Quantum Convolutional Neu...

Computer Vision and Machine Intelligence (CVMI), International Conference on

作者： Nasir Ali Abhishek Tiwari Rahul Kumar Neiwal Embedded Systems Division Centre for Development of Advanced Computing Noida India Electronics Division Ministry of Electronics and Information Technology New Delhi India

ISBN: (数字)9798350376876

ISBN: (纸本)9798350376883

This paper explores the innovative application of Quantum Convolutional Neural Networks (QCNN) in the classification of the MNIST fashion dataset. Quantum computing presents novel opportunities for enhancing machine learning algorithms, particularly in handling complex datasets. The MNIST fashion dataset is a large collection of Zalando’s article images, serves as an ideal candidate for demonstrating the efficacy of QCNN. This paper dives into the implementation of QCNN, compares QCNN’s performance with traditional neural networks, and further evaluates QCNN’s potential in revolutionizing image classification tasks in the realm of Quantum Machine Learning.

关键词： Computers Quantum computing Machine learning algorithms Computational modeling Scalability Neural networks Quantum mechanics Machine learning Convolutional neural networks Image classification

MV-Soccer: Motion-Vector Augmented Instance Segmentation for Soccer Player Tracking

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MV-Soccer: Motion-Vector Augmented Instance Segmentation for...

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Fahad Majeed Nauman Ullah Gilal Khaled Al-Thelaya Yin Yang Marco Agus Jens Schneider Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

This work presents a novel real-time detection, instance segmentation, and tracking approach for soccer videos. Unlike conventional methods, we augment video frames by incorporating motion vectors, thus adding valuable shape cues that are not readily present in RGB frames. This facilitates improved foreground/background separation and enhances the ability to distinguish between players, especially in scenarios involving partial occlusion. The proposed framework leverages the Cross-Stage-Partial Network53 (CSPDarknet53) as a backbone, for instance segmentation and integrates motion vectors, coupled with frame differencing. The model is simultaneously trained on two publicly available datasets and a private dataset, SoccerPro, which we created. The reason for simultaneous training is to reduce biases and increase generalization ability. To validate the effectiveness of our approach, we conducted extensive experiments and attained 97% accuracy for the DFL - Bundesliga Data Shootout, 98% on the SoccerNet-Tracking dataset, and an impressive 99% on the SoccerPro (our) dataset.

关键词： Instance segmentation Training Analytical models Accuracy Tracking Vectors Real-time systems

Meta Reinforcement Learning for Strategic IoT Deployments Coverage in Disaster-Response UAV Swarms

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arXiv 2024年

作者： Dhuheir, Marwan Erbad, Aiman Al-Fuqaha, Ala Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

In the past decade, Unmanned Aerial Vehicles (UAVs) have grabbed the attention of researchers in academia and industry for their potential use in critical emergency applications, such as providing wireless services to ground users and collecting data from areas affected by disasters, due to their advantages in terms of maneuverability and movement flexibility. The UAVs’ limited resources, energy budget, and strict mission completion time have posed challenges in adopting UAVs for these applications. Our system model considers a UAV swarm that navigates an area collecting data from ground IoT devices focusing on providing better service for strategic locations and allowing UAVs to join and leave the swarm (e.g., for recharging) in a dynamic way. In this work, we introduce an optimization model with the aim of minimizing the total energy consumption and provide the optimal path planning of UAVs under the constraints of minimum completion time and transmit power. The formulated optimization is NP-hard making it not applicable for real-time decision making. Therefore, we introduce a light-weight meta-reinforcement learning solution that can also cope with sudden changes in the environment through fast convergence. We conduct extensive simulations and compare our approach to three state-of-the-art learning models. Our simulation results prove that our introduced approach is better than the three state-of-the-art algorithms in providing coverage to strategic locations with fast convergence. © 2024, CC0.

关键词： Energy utilization

Performance Analysis of Underwater Acoustic Channel Amid Jamming by Random Jammers

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arXiv 2024年

作者： Aman, Waqas Al-Kuwari, Saif Qaraqe, Marwa The Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

Underwater communication networks are increasingly popularized by various important maritime applications. However, this also leads to an increased threat landscape. This letter presents the first study that considers jamming attacks by random jammers present in the surroundings of legitimate transceivers in underwater acoustic communication systems. We investigate the impact of jamming attacks on various performance parameters of the legitimate underwater acoustic communication link. In particular, we investigate the legitimate link using stochastic geometry for important performance parameters, namely coverage probability, average rate, and energy efficiency of the link between two legitimate nodes, i.e., underwater and surface nodes. We then derive and present tractable expressions for these performance parameters. Finally, we performed a Monte Carlo simulation to validate our analysis. We plot the performance metrics against the transmit power, and jamming power for different intensities of the jammers in shallow, mid, and deep water scenarios. Results reveal that on average, jamming in deep water has a relatively high impact on the performance of legitimate link than in shallow water. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

Toward Green and Flexible Human-Machine Interfaces: Personalized DIY Paper-Based Capacitive Macro Touchpads

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Toward Green and Flexible Human-Machine Interfaces: Personal...

International Conference on Microelectronics, ICM

作者： Muhammad Mateen Fawad Kashif Riaz Muhammad Hamza Zulfiqar Muhammad Nasir Arshad Khan Abdelkrim Khelif Department of Electrical Engineering Information Technology University of the Punjab Lahore Pakistan Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (数字)9798350379396

ISBN: (纸本)9798350379402

Plastic-based Human-Machine Interfaces (HMIs) offer convenience and affordability, but they often lack the customization options needed to cater to diverse user needs. In contrast, macro keypads and touchpads are gaining popularity due to their ability to be customized for specific tasks, form factor, software integration, and adaptability to various digital tasks, such as gaming, content creation, and productivity tasks. Due to their non-biodegradability and short serviceable lifespan, portable electronics and HMIs have significantly contributed to electronic waste (e-waste), with projections indicating that e-waste production will reach 110 million tonnes by 2050. To address these waste issues, green HMIs are needed that can be customized for various digital applications and have a minimal environmental footprint. This paper presents green paper-based capacitive macro (PCM) touchpads, customizable for various digital applications. The PCM touchpad's form factor can be tailored to specific needs, and its functionality can be personalized both digitally and through physical customization. The PCM touchpads, equipped with capacitive touch sensors, serve as versatile HMI, enabling seamless interaction with various digital applications on mobile devices and laptops. The PCM touchpads are manufactured using a simple, solvent-free, and environmentally friendly technique that involves directly cutting and pasting readily available materials onto a flexible paper substrate. This allows for easy customization and personalization of PCM touchpads for various applications within home settings, as required materials, such as paper, copper tape, and microcontrollers, are readily accessible. The PCM touchpads, made from biodegradable materials such as paper, can be easily disposed of, reused, recycled or repurposed, reducing their environmental impact. The performance of the PCM touchpad was evaluated by customizing it for a variety of digital applications, including a miniature

关键词： Phase change materials Electric potential Human-machine systems Green products Tactile sensors Games Electronic waste Software Sustainable development Substrates

On the Potential of Re-configurable Intelligent Surface (RIS)-assisted Physical Layer Authentication (PLA)

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arXiv 2024年

作者： Amin, Hala Aman, Waqas Al-Kuwari, Saif Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

Re-configurable Intelligent Surfaces (RIS) technology is increasingly becoming a potential component for next-generation wireless networks, offering enhanced performance in terms of throughput, spectral, and energy efficiency. However, the broadcast nature of RIS-assisted wireless communication makes it vulnerable to malicious attacks at the physical layer. At the same time, physical layer authentication is gaining popularity as a solution to secure wireless network, thwarting different attacks such as cloning, spoofing, and impersonation by using the random features of the physical layer. In this paper, we investigate RIS-assisted wireless communication systems to unlock the potential of using RIS for physical layer authentication (PLA). In particular, we exploit two distinct features of the physical layer: pathloss and channel impulse response (CIR) for PLA in RIS-assisted wireless communication. We construct hypothesis tests for the estimated features and derive closed-form error expressions. Further, we consider the critical error, i.e., missed detection, as our objective function to minimize by optimizing the phase shift of the RIS pannel. We compare the performance of our proposed mechanisms with PLA schemes using the same features but with no RIS. Furthermore, we thoroughly evaluate our proposed schemes using performance metrics such as the probability of false alarm (PFA), the probability of missed detection (PMD), and the receiver operating characteristic (ROC) curves. The results demonstrate clear positive impact of RIS on PLA, as it effectively reduces PMD values to zero when determining the optimal phase shift. Copyright © 2024, The Authors. All rights reserved.

关键词： Authentication

Recent Advances in Digital Image and Video Forensics, Anti-forensics and Counter Anti-forensics

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arXiv 2024年

作者： Al-Fehani, Maryam Al-Kuwari, Saif Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

Image and video forensics have recently gained increasing attention due to the proliferation of manipulated images and videos, especially on social media platforms, such as Twitter and Instagram, which spread disinformation and fake news. This survey explores image and video identification and forgery detection covering both manipulated digital media and generative media. However, media forgery detection techniques are susceptible to anti-forensics;on the other hand, such anti-forensics techniques can themselves be detected. We therefore further cover both anti-forensics and counter anti-forensics techniques in image and video. Finally, we conclude this survey by highlighting some open problems in this domain. © 2024, CC BY.

关键词： Digital storage

Modelling Population-Level Hes1 Dynamics: Insights from a Multi-Framework Approach

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arXiv 2024年

作者： Menz, Gesina Engblom, Stefan Division of Scientific Computing Department of Information Technology Uppsala University UppsalaSE-751 05 Sweden Science for Life Laboratory Department of Information Technology Uppsala University Sweden

Mathematical models of living cells have been successively refined with advancements in experimental techniques. A main concern is striking a balance between modelling power and the tractability of the associated mathematical analysis. In this work we model the dynamics for the transcription factor Hairy and enhancer of split-1 (Hes1), whose expression oscillates during neural development, and which critically enables stable fate decision in the embryonic brain. We design, parametrise, and analyse a detailed spatial model using ordinary differential equations (ODEs) over a grid capturing both transient oscillatory behaviour and fate decision on a population-level. We also investigate the relationship between this ODE model and a more realistic grid-based model involving intrinsic noise using mostly directly biologically motivated parameters. While we focus specifically on Hes1 in neural development, the approach of linking deterministic and stochastic grid-based models shows promise in modelling various biological processes taking place in a cell population. In this context, our work stresses the importance of the interpretability of complex computational models into a framework which is amenable to mathematical analysis. © 2024, CC BY.

关键词： Analytical models

Explainable Artificial Intelligence Solution for Online Retail

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Computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan Department of Computer Science University of South AsiaLahore54000Pakistan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the *** permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

关键词： Explainable artificial intelligence online retail neural network random forest regression